{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication\AshMorelliVannoni_PSRM2020.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 5 Aug 2020, 09:49:48
{txt}
{com}. 
. use "AshMorelliVannoni_PSRM2020.dta", clear
{txt}(Written by R.              )

{com}. 
. xtset state year, yearly delta(1)
{res}{txt}{col 8}panel variable:  {res}state (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}year, 1965 to 1983
{txt}{col 17}delta:  {res}1 year
{txt}
{com}. 
. 
. 
. *// Table 1 
. 
. reghdfe civil_service_reform_ipe divided_either , a( state  )    cl(state ) 
{res}{txt}(existing lftools.mlib compiled with Stata ???; need to recompile for Stata 15.1)
(compiling lftools.mlib for Stata 15.1)
(library saved in C:\users\PUBLIC\documents/l/lftools.mlib)
{res}{txt}(existing lreghdfe.mlib compiled with Stata ???; need to recompile for Stata 15.1)
(compiling lreghdfe.mlib for Stata 15.1)
(library saved in C:\users\PUBLIC\documents/l/lreghdfe.mlib)
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 1 HDFE group{col 51}F({res}   1{txt},{res}     46{txt}){col 67}= {res}      5.85
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0195
{txt}{col 51}R-squared{col 67}= {res}    0.6076
{txt}{col 51}Adj R-squared{col 67}= {res}    0.5840
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0121
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4361

{txt}{ralign 80:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}civil_servic~e{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_either {c |}{col 16}{res}{space 2} .1090287{col 28}{space 2} .0450588{col 39}{space 1}    2.42{col 48}{space 3}0.020{col 56}{space 4} .0183302{col 69}{space 3} .1997273
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 1.300686{col 28}{space 2} .0206293{col 39}{space 1}   63.05{col 48}{space 3}0.000{col 56}{space 4} 1.259161{col 69}{space 3}  1.34221
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table1, tex replace keep(divided_either) label   ctitle(Merit IPE)    addtext(State FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{txt}{stata `"shellout using `"Table1.tex"'"':Table1.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table1.txt", label"':seeout}

{com}. 
. reghdfe civil_service_reform_ipe divided_either , a(state year   )    cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   1{txt},{res}     46{txt}){col 67}= {res}      5.88
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0193
{txt}{col 51}R-squared{col 67}= {res}    0.6312
{txt}{col 51}Adj R-squared{col 67}= {res}    0.5993
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0130
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4280

{txt}{ralign 80:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}civil_servic~e{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_either {c |}{col 16}{res}{space 2} .1104086{col 28}{space 2} .0455347{col 39}{space 1}    2.42{col 48}{space 3}0.019{col 56}{space 4}  .018752{col 69}{space 3} .2020652
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 1.300054{col 28}{space 2} .0208472{col 39}{space 1}   62.36{col 48}{space 3}0.000{col 56}{space 4} 1.258091{col 69}{space 3} 1.342017
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table1, tex append keep(divided_either)  label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table1.tex"'"':Table1.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table1.txt", label"':seeout}

{com}. 
. reghdfe civil_service_reform_ipe true_divided_gov_a, a(state year)   cl(state) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   1{txt},{res}     46{txt}){col 67}= {res}      8.68
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0050
{txt}{col 51}R-squared{col 67}= {res}    0.6328
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6011
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0174
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4270

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_a {c |}{col 20}{res}{space 2} .1488385{col 32}{space 2} .0505078{col 43}{space 1}    2.95{col 52}{space 3}0.005{col 60}{space 4} .0471715{col 73}{space 3} .2505054
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.300213{col 32}{space 2} .0170996{col 43}{space 1}   76.04{col 52}{space 3}0.000{col 60}{space 4} 1.265793{col 73}{space 3} 1.334632
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table1, tex append keep(true_divided_gov_a) label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table1.tex"'"':Table1.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table1.txt", label"':seeout}

{com}. 
. reghdfe civil_service_reform_ipe divided_either ideociti urban income  lfullemp , a(state year)   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   5{txt},{res}     46{txt}){col 67}= {res}      4.18
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0033
{txt}{col 51}R-squared{col 67}= {res}    0.6580
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6265
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0848
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4132

{txt}{ralign 80:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}civil_servic~e{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_either {c |}{col 16}{res}{space 2} .0931154{col 28}{space 2}  .045387{col 39}{space 1}    2.05{col 48}{space 3}0.046{col 56}{space 4} .0017562{col 69}{space 3} .1844746
{txt}{space 6}ideociti {c |}{col 16}{res}{space 2} 1.190693{col 28}{space 2} .4343644{col 39}{space 1}    2.74{col 48}{space 3}0.009{col 56}{space 4}  .316363{col 69}{space 3} 2.065023
{txt}{space 9}urban {c |}{col 16}{res}{space 2} 6.815772{col 28}{space 2} 3.560686{col 39}{space 1}    1.91{col 48}{space 3}0.062{col 56}{space 4}-.3515171{col 69}{space 3} 13.98306
{txt}{space 8}income {c |}{col 16}{res}{space 2} -.001101{col 28}{space 2} .0629289{col 39}{space 1}   -0.02{col 48}{space 3}0.986{col 56}{space 4}-.1277703{col 69}{space 3} .1255684
{txt}{space 6}lfullemp {c |}{col 16}{res}{space 2}-.5182807{col 28}{space 2} .5719809{col 39}{space 1}   -0.91{col 48}{space 3}0.370{col 56}{space 4}-1.669619{col 69}{space 3} .6330572
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 1.751738{col 28}{space 2} 5.650961{col 39}{space 1}    0.31{col 48}{space 3}0.758{col 56}{space 4}-9.623056{col 69}{space 3} 13.12653
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table1, tex append keep(divided_either ideociti urban income  lfullemp ) label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table1.tex"'"':Table1.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table1.txt", label"':seeout}

{com}. 
. reghdfe civil_service_reform_ipe divided_either ideociti urban income  lfullemp, a(state##c.year year)   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 6 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   5{txt},{res}     46{txt}){col 67}= {res}      2.13
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0786
{txt}{col 51}R-squared{col 67}= {res}    0.8383
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8117
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0238
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.2934

{txt}{ralign 80:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}civil_servic~e{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_either {c |}{col 16}{res}{space 2} .0534537{col 28}{space 2} .0374277{col 39}{space 1}    1.43{col 48}{space 3}0.160{col 56}{space 4}-.0218843{col 69}{space 3} .1287917
{txt}{space 6}ideociti {c |}{col 16}{res}{space 2} .6161245{col 28}{space 2} .2497685{col 39}{space 1}    2.47{col 48}{space 3}0.017{col 56}{space 4} .1133666{col 69}{space 3} 1.118882
{txt}{space 9}urban {c |}{col 16}{res}{space 2} 3.802784{col 28}{space 2} 8.032727{col 39}{space 1}    0.47{col 48}{space 3}0.638{col 56}{space 4}-12.36626{col 69}{space 3} 19.97183
{txt}{space 8}income {c |}{col 16}{res}{space 2} .0398196{col 28}{space 2} .0826177{col 39}{space 1}    0.48{col 48}{space 3}0.632{col 56}{space 4}-.1264812{col 69}{space 3} .2061203
{txt}{space 6}lfullemp {c |}{col 16}{res}{space 2}    .2354{col 28}{space 2} .3709384{col 39}{space 1}    0.63{col 48}{space 3}0.529{col 56}{space 4}-.5112603{col 69}{space 3} .9820603
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}-4.328489{col 28}{space 2} 6.516384{col 39}{space 1}   -0.66{col 48}{space 3}0.510{col 56}{space 4}-17.44529{col 69}{space 3} 8.788311
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 14}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}  Absorbed FE{col 15}{c |} Categories{col 28} - Redundant{col 40}  = Num. Coefs{col 55}{c |}
{res}{col 1}{text}{hline 14}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text} state#c.year{col 15}{c |}{space 1}       47{col 28}{space 1}        0{col 40}{result}{space 1}       47{col 54}{text} {col 55}{c |}
{res}{col 1}{text}         year{col 15}{c |}{space 1}       19{col 28}{space 1}        0{col 40}{result}{space 1}       19{col 54}{text}?{col 55}{c |}
{res}{col 1}{text}{hline 14}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table1, tex append keep(divided_either ideociti urban income  lfullemp) label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X,  State-Specific Trends, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table1.tex"'"':Table1.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table1.txt", label"':seeout}

{com}. 
. ologit civil_service_reform_ipe divided_either ideociti urban income  lfullemp i.year  i.state ,   cl(state) 

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -803.7917}  
Iteration 1:{space 3}log pseudolikelihood = {res:-415.09165}  
Iteration 2:{space 3}log pseudolikelihood = {res:-381.56683}  
Iteration 3:{space 3}log pseudolikelihood = {res: -374.8177}  
Iteration 4:{space 3}log pseudolikelihood = {res:-373.96714}  
Iteration 5:{space 3}log pseudolikelihood = {res:-373.75711}  
Iteration 6:{space 3}log pseudolikelihood = {res:-373.71456}  
Iteration 7:{space 3}log pseudolikelihood = {res:-373.70536}  
Iteration 8:{space 3}log pseudolikelihood = {res: -373.7033}  
Iteration 9:{space 3}log pseudolikelihood = {res:-373.70278}  
Iteration 10:{space 2}log pseudolikelihood = {res:-373.70268}  
Iteration 11:{space 2}log pseudolikelihood = {res:-373.70266}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       830
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(28)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-373.70266{txt}{col 49}Pseudo R2{col 67}= {res}    0.5351

{txt}{ralign 90:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}civil_service_reform_ipe{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}divided_either {c |}{col 26}{res}{space 2} .5586252{col 38}{space 2} .3059045{col 49}{space 1}    1.83{col 58}{space 3}0.068{col 66}{space 4}-.0409367{col 79}{space 3} 1.158187
{txt}{space 16}ideociti {c |}{col 26}{res}{space 2} 8.141755{col 38}{space 2} 2.874386{col 49}{space 1}    2.83{col 58}{space 3}0.005{col 66}{space 4} 2.508062{col 79}{space 3} 13.77545
{txt}{space 19}urban {c |}{col 26}{res}{space 2} 45.32628{col 38}{space 2} 29.54505{col 49}{space 1}    1.53{col 58}{space 3}0.125{col 66}{space 4}-12.58096{col 79}{space 3} 103.2335
{txt}{space 18}income {c |}{col 26}{res}{space 2}-.0987088{col 38}{space 2} .4492159{col 49}{space 1}   -0.22{col 58}{space 3}0.826{col 66}{space 4}-.9791557{col 79}{space 3} .7817381
{txt}{space 16}lfullemp {c |}{col 26}{res}{space 2}-2.677704{col 38}{space 2} 4.174666{col 49}{space 1}   -0.64{col 58}{space 3}0.521{col 66}{space 4} -10.8599{col 79}{space 3} 5.504491
{txt}{space 24} {c |}
{space 20}year {c |}
{space 19}1966  {c |}{col 26}{res}{space 2} .3908763{col 38}{space 2} .4158199{col 49}{space 1}    0.94{col 58}{space 3}0.347{col 66}{space 4}-.4241158{col 79}{space 3} 1.205868
{txt}{space 19}1967  {c |}{col 26}{res}{space 2}  .608181{col 38}{space 2} .6627653{col 49}{space 1}    0.92{col 58}{space 3}0.359{col 66}{space 4}-.6908151{col 79}{space 3} 1.907177
{txt}{space 19}1968  {c |}{col 26}{res}{space 2} .6286034{col 38}{space 2} .9850165{col 49}{space 1}    0.64{col 58}{space 3}0.523{col 66}{space 4}-1.301993{col 79}{space 3}   2.5592
{txt}{space 19}1969  {c |}{col 26}{res}{space 2} 1.171289{col 38}{space 2}  1.09127{col 49}{space 1}    1.07{col 58}{space 3}0.283{col 66}{space 4}-.9675609{col 79}{space 3} 3.310139
{txt}{space 19}1970  {c |}{col 26}{res}{space 2} 1.206294{col 38}{space 2} 1.258734{col 49}{space 1}    0.96{col 58}{space 3}0.338{col 66}{space 4}-1.260778{col 79}{space 3} 3.673367
{txt}{space 19}1971  {c |}{col 26}{res}{space 2} .7292175{col 38}{space 2} 1.408224{col 49}{space 1}    0.52{col 58}{space 3}0.605{col 66}{space 4}-2.030852{col 79}{space 3} 3.489287
{txt}{space 19}1972  {c |}{col 26}{res}{space 2} 1.376555{col 38}{space 2} 1.786902{col 49}{space 1}    0.77{col 58}{space 3}0.441{col 66}{space 4}-2.125708{col 79}{space 3} 4.878818
{txt}{space 19}1973  {c |}{col 26}{res}{space 2} 1.362854{col 38}{space 2} 2.067154{col 49}{space 1}    0.66{col 58}{space 3}0.510{col 66}{space 4}-2.688692{col 79}{space 3} 5.414401
{txt}{space 19}1974  {c |}{col 26}{res}{space 2} 1.555068{col 38}{space 2} 2.145495{col 49}{space 1}    0.72{col 58}{space 3}0.469{col 66}{space 4}-2.650026{col 79}{space 3} 5.760162
{txt}{space 19}1975  {c |}{col 26}{res}{space 2} 1.570481{col 38}{space 2} 2.338103{col 49}{space 1}    0.67{col 58}{space 3}0.502{col 66}{space 4}-3.012116{col 79}{space 3} 6.153078
{txt}{space 19}1976  {c |}{col 26}{res}{space 2} 2.218531{col 38}{space 2} 2.390055{col 49}{space 1}    0.93{col 58}{space 3}0.353{col 66}{space 4} -2.46589{col 79}{space 3} 6.902953
{txt}{space 19}1977  {c |}{col 26}{res}{space 2} 2.332597{col 38}{space 2} 2.562989{col 49}{space 1}    0.91{col 58}{space 3}0.363{col 66}{space 4} -2.69077{col 79}{space 3} 7.355964
{txt}{space 19}1978  {c |}{col 26}{res}{space 2} 2.442559{col 38}{space 2} 2.735861{col 49}{space 1}    0.89{col 58}{space 3}0.372{col 66}{space 4}-2.919629{col 79}{space 3} 7.804747
{txt}{space 19}1979  {c |}{col 26}{res}{space 2} 2.319847{col 38}{space 2} 2.873666{col 49}{space 1}    0.81{col 58}{space 3}0.420{col 66}{space 4}-3.312435{col 79}{space 3}  7.95213
{txt}{space 19}1980  {c |}{col 26}{res}{space 2} 2.336622{col 38}{space 2} 2.815815{col 49}{space 1}    0.83{col 58}{space 3}0.407{col 66}{space 4}-3.182275{col 79}{space 3} 7.855519
{txt}{space 19}1981  {c |}{col 26}{res}{space 2} 2.531105{col 38}{space 2} 2.794558{col 49}{space 1}    0.91{col 58}{space 3}0.365{col 66}{space 4}-2.946128{col 79}{space 3} 8.008338
{txt}{space 19}1982  {c |}{col 26}{res}{space 2} 1.850578{col 38}{space 2} 2.752788{col 49}{space 1}    0.67{col 58}{space 3}0.501{col 66}{space 4}-3.544788{col 79}{space 3} 7.245944
{txt}{space 19}1983  {c |}{col 26}{res}{space 2} 1.811284{col 38}{space 2} 2.727481{col 49}{space 1}    0.66{col 58}{space 3}0.507{col 66}{space 4}-3.534481{col 79}{space 3} 7.157048
{txt}{space 24} {c |}
{space 19}state {c |}
{space 21}AR  {c |}{col 26}{res}{space 2}-15.54014{col 38}{space 2} 2.894514{col 49}{space 1}   -5.37{col 58}{space 3}0.000{col 66}{space 4}-21.21328{col 79}{space 3}-9.866998
{txt}{space 21}AZ  {c |}{col 26}{res}{space 2}-29.54927{col 38}{space 2} 7.363372{col 49}{space 1}   -4.01{col 58}{space 3}0.000{col 66}{space 4}-43.98122{col 79}{space 3}-15.11733
{txt}{space 21}CA  {c |}{col 26}{res}{space 2}-31.04546{col 38}{space 2} 9.349628{col 49}{space 1}   -3.32{col 58}{space 3}0.001{col 66}{space 4} -49.3704{col 79}{space 3}-12.72053
{txt}{space 21}CO  {c |}{col 26}{res}{space 2}-31.99951{col 38}{space 2} 6.077568{col 49}{space 1}   -5.27{col 58}{space 3}0.000{col 66}{space 4}-43.91133{col 79}{space 3} -20.0877
{txt}{space 21}CT  {c |}{col 26}{res}{space 2}-31.58446{col 38}{space 2} 5.739149{col 49}{space 1}   -5.50{col 58}{space 3}0.000{col 66}{space 4}-42.83298{col 79}{space 3}-20.33593
{txt}{space 21}DE  {c |}{col 26}{res}{space 2} -31.6927{col 38}{space 2} 6.827824{col 49}{space 1}   -4.64{col 58}{space 3}0.000{col 66}{space 4}-45.07499{col 79}{space 3}-18.31041
{txt}{space 21}FL  {c |}{col 26}{res}{space 2}-26.23376{col 38}{space 2} 6.382593{col 49}{space 1}   -4.11{col 58}{space 3}0.000{col 66}{space 4}-38.74341{col 79}{space 3}-13.72411
{txt}{space 21}GA  {c |}{col 26}{res}{space 2}-17.84511{col 38}{space 2} 1.957499{col 49}{space 1}   -9.12{col 58}{space 3}0.000{col 66}{space 4}-21.68174{col 79}{space 3}-14.00849
{txt}{space 21}IA  {c |}{col 26}{res}{space 2}-17.93718{col 38}{space 2} 2.171214{col 49}{space 1}   -8.26{col 58}{space 3}0.000{col 66}{space 4}-22.19268{col 79}{space 3}-13.68168
{txt}{space 21}ID  {c |}{col 26}{res}{space 2}-19.70926{col 38}{space 2} 5.248584{col 49}{space 1}   -3.76{col 58}{space 3}0.000{col 66}{space 4}-29.99629{col 79}{space 3}-9.422219
{txt}{space 21}IL  {c |}{col 26}{res}{space 2}-31.43211{col 38}{space 2} 6.748983{col 49}{space 1}   -4.66{col 58}{space 3}0.000{col 66}{space 4}-44.65987{col 79}{space 3}-18.20435
{txt}{space 21}IN  {c |}{col 26}{res}{space 2}-22.33241{col 38}{space 2} 2.245759{col 49}{space 1}   -9.94{col 58}{space 3}0.000{col 66}{space 4}-26.73401{col 79}{space 3} -17.9308
{txt}{space 21}KS  {c |}{col 26}{res}{space 2}-6.099367{col 38}{space 2} 3.004328{col 49}{space 1}   -2.03{col 58}{space 3}0.042{col 66}{space 4}-11.98774{col 79}{space 3}-.2109927
{txt}{space 21}KY  {c |}{col 26}{res}{space 2}-18.38698{col 38}{space 2} 3.024514{col 49}{space 1}   -6.08{col 58}{space 3}0.000{col 66}{space 4}-24.31492{col 79}{space 3}-12.45904
{txt}{space 21}LA  {c |}{col 26}{res}{space 2}-3.076682{col 38}{space 2} 2.870707{col 49}{space 1}   -1.07{col 58}{space 3}0.284{col 66}{space 4}-8.703164{col 79}{space 3}   2.5498
{txt}{space 21}MA  {c |}{col 26}{res}{space 2}-15.20331{col 38}{space 2} 7.021701{col 49}{space 1}   -2.17{col 58}{space 3}0.030{col 66}{space 4} -28.9656{col 79}{space 3}-1.441033
{txt}{space 21}MD  {c |}{col 26}{res}{space 2} -31.1308{col 38}{space 2} 5.334466{col 49}{space 1}   -5.84{col 58}{space 3}0.000{col 66}{space 4}-41.58616{col 79}{space 3}-20.67544
{txt}{space 21}ME  {c |}{col 26}{res}{space 2}-19.54413{col 38}{space 2} 4.668239{col 49}{space 1}   -4.19{col 58}{space 3}0.000{col 66}{space 4}-28.69371{col 79}{space 3}-10.39455
{txt}{space 21}MI  {c |}{col 26}{res}{space 2}-7.589625{col 38}{space 2} 4.570093{col 49}{space 1}   -1.66{col 58}{space 3}0.097{col 66}{space 4}-16.54684{col 79}{space 3} 1.367593
{txt}{space 21}MN  {c |}{col 26}{res}{space 2}-24.68081{col 38}{space 2} 2.757047{col 49}{space 1}   -8.95{col 58}{space 3}0.000{col 66}{space 4}-30.08452{col 79}{space 3} -19.2771
{txt}{space 21}MO  {c |}{col 26}{res}{space 2}-24.12872{col 38}{space 2} 3.064892{col 49}{space 1}   -7.87{col 58}{space 3}0.000{col 66}{space 4} -30.1358{col 79}{space 3}-18.12165
{txt}{space 21}MS  {c |}{col 26}{res}{space 2}-17.52436{col 38}{space 2} 3.786766{col 49}{space 1}   -4.63{col 58}{space 3}0.000{col 66}{space 4}-24.94628{col 79}{space 3}-10.10243
{txt}{space 21}MT  {c |}{col 26}{res}{space 2}-24.58913{col 38}{space 2} 5.040133{col 49}{space 1}   -4.88{col 58}{space 3}0.000{col 66}{space 4}-34.46761{col 79}{space 3}-14.71065
{txt}{space 21}NC  {c |}{col 26}{res}{space 2} 7.506964{col 38}{space 2} 5.298124{col 49}{space 1}    1.42{col 58}{space 3}0.157{col 66}{space 4}-2.877168{col 79}{space 3}  17.8911
{txt}{space 21}ND  {c |}{col 26}{res}{space 2}-22.33266{col 38}{space 2} 6.391299{col 49}{space 1}   -3.49{col 58}{space 3}0.000{col 66}{space 4}-34.85937{col 79}{space 3}-9.805944
{txt}{space 21}NH  {c |}{col 26}{res}{space 2}-18.43721{col 38}{space 2} 5.752937{col 49}{space 1}   -3.20{col 58}{space 3}0.001{col 66}{space 4}-29.71276{col 79}{space 3}-7.161657
{txt}{space 21}NJ  {c |}{col 26}{res}{space 2}-35.87356{col 38}{space 2} 8.151838{col 49}{space 1}   -4.40{col 58}{space 3}0.000{col 66}{space 4}-51.85087{col 79}{space 3}-19.89625
{txt}{space 21}NM  {c |}{col 26}{res}{space 2}-25.68405{col 38}{space 2} 5.081185{col 49}{space 1}   -5.05{col 58}{space 3}0.000{col 66}{space 4}-35.64299{col 79}{space 3}-15.72511
{txt}{space 21}NV  {c |}{col 26}{res}{space 2}-14.76463{col 38}{space 2} 10.45072{col 49}{space 1}   -1.41{col 58}{space 3}0.158{col 66}{space 4}-35.24766{col 79}{space 3} 5.718405
{txt}{space 21}NY  {c |}{col 26}{res}{space 2}-31.74559{col 38}{space 2}  8.25621{col 49}{space 1}   -3.85{col 58}{space 3}0.000{col 66}{space 4}-47.92746{col 79}{space 3}-15.56372
{txt}{space 21}OH  {c |}{col 26}{res}{space 2}-25.95063{col 38}{space 2} 4.802504{col 49}{space 1}   -5.40{col 58}{space 3}0.000{col 66}{space 4}-35.36337{col 79}{space 3} -16.5379
{txt}{space 21}OK  {c |}{col 26}{res}{space 2}-5.039986{col 38}{space 2} 2.839518{col 49}{space 1}   -1.77{col 58}{space 3}0.076{col 66}{space 4}-10.60534{col 79}{space 3} .5253677
{txt}{space 21}OR  {c |}{col 26}{res}{space 2}-26.68896{col 38}{space 2} 3.262515{col 49}{space 1}   -8.18{col 58}{space 3}0.000{col 66}{space 4}-33.08337{col 79}{space 3}-20.29455
{txt}{space 21}PA  {c |}{col 26}{res}{space 2}-23.92161{col 38}{space 2} 5.195087{col 49}{space 1}   -4.60{col 58}{space 3}0.000{col 66}{space 4}-34.10379{col 79}{space 3}-13.73943
{txt}{space 21}RI  {c |}{col 26}{res}{space 2}-36.71827{col 38}{space 2} 10.05479{col 49}{space 1}   -3.65{col 58}{space 3}0.000{col 66}{space 4} -56.4253{col 79}{space 3}-17.01125
{txt}{space 21}SC  {c |}{col 26}{res}{space 2}-13.43068{col 38}{space 2} 2.925582{col 49}{space 1}   -4.59{col 58}{space 3}0.000{col 66}{space 4}-19.16471{col 79}{space 3}-7.696646
{txt}{space 21}SD  {c |}{col 26}{res}{space 2}-22.12043{col 38}{space 2} 6.298285{col 49}{space 1}   -3.51{col 58}{space 3}0.000{col 66}{space 4}-34.46484{col 79}{space 3} -9.77602
{txt}{space 21}TN  {c |}{col 26}{res}{space 2}-21.42254{col 38}{space 2} 1.804027{col 49}{space 1}  -11.87{col 58}{space 3}0.000{col 66}{space 4}-24.95837{col 79}{space 3}-17.88671
{txt}{space 21}TX  {c |}{col 26}{res}{space 2}-54.21311{col 38}{space 2} 6.421054{col 49}{space 1}   -8.44{col 58}{space 3}0.000{col 66}{space 4}-66.79815{col 79}{space 3}-41.62808
{txt}{space 21}UT  {c |}{col 26}{res}{space 2}-28.75484{col 38}{space 2} 7.986558{col 49}{space 1}   -3.60{col 58}{space 3}0.000{col 66}{space 4} -44.4082{col 79}{space 3}-13.10147
{txt}{space 21}VA  {c |}{col 26}{res}{space 2}-20.83596{col 38}{space 2} 2.709153{col 49}{space 1}   -7.69{col 58}{space 3}0.000{col 66}{space 4} -26.1458{col 79}{space 3}-15.52612
{txt}{space 21}VT  {c |}{col 26}{res}{space 2}-14.75953{col 38}{space 2} 8.630538{col 49}{space 1}   -1.71{col 58}{space 3}0.087{col 66}{space 4}-31.67507{col 79}{space 3} 2.156013
{txt}{space 21}WA  {c |}{col 26}{res}{space 2}-29.47702{col 38}{space 2} 4.105654{col 49}{space 1}   -7.18{col 58}{space 3}0.000{col 66}{space 4}-37.52395{col 79}{space 3}-21.43009
{txt}{space 21}WI  {c |}{col 26}{res}{space 2}-21.24687{col 38}{space 2} 2.424776{col 49}{space 1}   -8.76{col 58}{space 3}0.000{col 66}{space 4}-25.99935{col 79}{space 3} -16.4944
{txt}{space 21}WV  {c |}{col 26}{res}{space 2}-41.44871{col 38}{space 2} 6.371854{col 49}{space 1}   -6.50{col 58}{space 3}0.000{col 66}{space 4}-53.93731{col 79}{space 3} -28.9601
{txt}{space 21}WY  {c |}{col 26}{res}{space 2}-26.93807{col 38}{space 2} 7.656079{col 49}{space 1}   -3.52{col 58}{space 3}0.000{col 66}{space 4}-41.94371{col 79}{space 3}-11.93243
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}/cut1 {c |}{col 26}{res}{space 2}-22.15247{col 38}{space 2} 40.81028{col 66}{space 4}-102.1391{col 79}{space 3}  57.8342
{txt}{space 19}/cut2 {c |}{col 26}{res}{space 2}-17.42384{col 38}{space 2} 40.84332{col 66}{space 4}-97.47528{col 79}{space 3}  62.6276
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 188 observations completely determined.{txt}  Standard errors questionable.{p_end}

{com}. outreg2 using Table1, tex append keep(divided_either ideociti urban income  lfullemp) label   ctitle(Merit IPE - Ologit)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table1.tex"'"':Table1.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table1.txt", label"':seeout}

{com}. 
. reghdfe civil_service_reform divided_either ideociti urban income  lfullemp, a(state year )     cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       893
{txt}Absorbing 2 HDFE groups{col 51}F({res}   5{txt},{res}     46{txt}){col 67}= {res}      3.47
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0097
{txt}{col 51}R-squared{col 67}= {res}    0.7041
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6789
{txt}{col 51}Within R-sq.{col 67}= {res}    0.1233
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.1748

{txt}{ralign 80:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}civil_servic~m{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_either {c |}{col 16}{res}{space 2} .0104529{col 28}{space 2} .0142763{col 39}{space 1}    0.73{col 48}{space 3}0.468{col 56}{space 4}-.0182839{col 69}{space 3} .0391897
{txt}{space 6}ideociti {c |}{col 16}{res}{space 2} .2648449{col 28}{space 2}  .184126{col 39}{space 1}    1.44{col 48}{space 3}0.157{col 56}{space 4}-.1057815{col 69}{space 3} .6354713
{txt}{space 9}urban {c |}{col 16}{res}{space 2} 5.501225{col 28}{space 2} 1.781063{col 39}{space 1}    3.09{col 48}{space 3}0.003{col 56}{space 4} 1.916131{col 69}{space 3} 9.086318
{txt}{space 8}income {c |}{col 16}{res}{space 2} -.019082{col 28}{space 2} .0272991{col 39}{space 1}   -0.70{col 48}{space 3}0.488{col 56}{space 4}-.0740322{col 69}{space 3} .0358683
{txt}{space 6}lfullemp {c |}{col 16}{res}{space 2}-.3802173{col 28}{space 2}    .2483{col 39}{space 1}   -1.53{col 48}{space 3}0.133{col 56}{space 4}-.8800193{col 69}{space 3} .1195847
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 1.330111{col 28}{space 2} 2.079362{col 39}{space 1}    0.64{col 48}{space 3}0.526{col 56}{space 4}-2.855429{col 69}{space 3}  5.51565
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table1, tex append keep(divided_either ideociti urban income  lfullemp ) label   ctitle(Merit)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table1.tex"'"':Table1.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table1.txt", label"':seeout}

{com}. 
. *// Table 2
. 
. reghdfe civil_service_reform_ipe divided_governor divided_chamber , a(state  )   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 1 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 1 HDFE group{col 51}F({res}   2{txt},{res}     46{txt}){col 67}= {res}      3.03
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0582
{txt}{col 51}R-squared{col 67}= {res}    0.6076
{txt}{col 51}Adj R-squared{col 67}= {res}    0.5835
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0122
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4364

{txt}{ralign 82:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}civil_service_~e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_governor {c |}{col 18}{res}{space 2} .1122858{col 30}{space 2} .0531186{col 41}{space 1}    2.11{col 50}{space 3}0.040{col 58}{space 4} .0053636{col 71}{space 3} .2192081
{txt}{space 1}divided_chamber {c |}{col 18}{res}{space 2} .1012822{col 30}{space 2} .0556569{col 41}{space 1}    1.82{col 50}{space 3}0.075{col 58}{space 4}-.0107494{col 71}{space 3} .2133137
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.300891{col 30}{space 2} .0203558{col 41}{space 1}   63.91{col 50}{space 3}0.000{col 58}{space 4} 1.259917{col 71}{space 3} 1.341866
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table2, tex replace keep(divided_governor divided_chamber ) label   ctitle(Merit IPE)    addtext(State FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{txt}{stata `"shellout using `"Table2.tex"'"':Table2.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table2.txt", label"':seeout}

{com}. 
. reghdfe civil_service_reform_ipe divided_governor divided_chamber , a(state year )   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   2{txt},{res}     46{txt}){col 67}= {res}      3.28
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0465
{txt}{col 51}R-squared{col 67}= {res}    0.6312
{txt}{col 51}Adj R-squared{col 67}= {res}    0.5988
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0130
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4283

{txt}{ralign 82:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}civil_service_~e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_governor {c |}{col 18}{res}{space 2} .1099458{col 30}{space 2} .0581393{col 41}{space 1}    1.89{col 50}{space 3}0.065{col 58}{space 4}-.0070827{col 71}{space 3} .2269742
{txt}{space 1}divided_chamber {c |}{col 18}{res}{space 2} .1114877{col 30}{space 2} .0604954{col 41}{space 1}    1.84{col 50}{space 3}0.072{col 58}{space 4}-.0102833{col 71}{space 3} .2332586
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.300028{col 30}{space 2} .0204698{col 41}{space 1}   63.51{col 50}{space 3}0.000{col 58}{space 4} 1.258824{col 71}{space 3} 1.341232
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table2, tex append keep(divided_governor divided_chamber)  label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table2.tex"'"':Table2.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table2.txt", label"':seeout}

{com}. 
. reghdfe civil_service_reform_ipe divided_governor divided_chamber ideociti urban income  lfullemp, a(state year )   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   6{txt},{res}     46{txt}){col 67}= {res}      3.69
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0045
{txt}{col 51}R-squared{col 67}= {res}    0.6585
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6265
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0861
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4132

{txt}{ralign 82:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}civil_service_~e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_governor {c |}{col 18}{res}{space 2} .0764952{col 30}{space 2} .0556902{col 41}{space 1}    1.37{col 50}{space 3}0.176{col 58}{space 4}-.0356034{col 71}{space 3} .1885939
{txt}{space 1}divided_chamber {c |}{col 18}{res}{space 2}  .129952{col 30}{space 2} .0584166{col 41}{space 1}    2.22{col 50}{space 3}0.031{col 58}{space 4} .0123654{col 71}{space 3} .2475386
{txt}{space 8}ideociti {c |}{col 18}{res}{space 2}  1.19194{col 30}{space 2} .4359156{col 41}{space 1}    2.73{col 50}{space 3}0.009{col 58}{space 4} .3144879{col 71}{space 3} 2.069393
{txt}{space 11}urban {c |}{col 18}{res}{space 2} 7.019505{col 30}{space 2} 3.616776{col 41}{space 1}    1.94{col 50}{space 3}0.058{col 58}{space 4}-.2606864{col 71}{space 3}  14.2997
{txt}{space 10}income {c |}{col 18}{res}{space 2} .0048845{col 30}{space 2} .0630844{col 41}{space 1}    0.08{col 50}{space 3}0.939{col 58}{space 4}-.1220977{col 71}{space 3} .1318668
{txt}{space 8}lfullemp {c |}{col 18}{res}{space 2}-.5406173{col 30}{space 2} .5786193{col 41}{space 1}   -0.93{col 50}{space 3}0.355{col 58}{space 4}-1.705317{col 71}{space 3} .6240829
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.787048{col 30}{space 2} 5.667088{col 41}{space 1}    0.32{col 50}{space 3}0.754{col 58}{space 4} -9.62021{col 71}{space 3} 13.19431
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table2, tex append keep(divided_governor divided_chamber ideociti urban income  lfullemp) label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table2.tex"'"':Table2.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table2.txt", label"':seeout}

{com}. 
. reghdfe civil_service_reform_ipe divided_governor divided_chamber ideociti urban income  lfullemp , a(state##c.year year )   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 6 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   6{txt},{res}     46{txt}){col 67}= {res}      2.38
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0440
{txt}{col 51}R-squared{col 67}= {res}    0.8384
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8116
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0244
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.2935

{txt}{ralign 82:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}civil_service_~e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_governor {c |}{col 18}{res}{space 2} .0438244{col 30}{space 2} .0452957{col 41}{space 1}    0.97{col 50}{space 3}0.338{col 58}{space 4}-.0473511{col 71}{space 3} .1349999
{txt}{space 1}divided_chamber {c |}{col 18}{res}{space 2} .0712438{col 30}{space 2}  .039673{col 41}{space 1}    1.80{col 50}{space 3}0.079{col 58}{space 4}-.0086139{col 71}{space 3} .1511015
{txt}{space 8}ideociti {c |}{col 18}{res}{space 2} .6140292{col 30}{space 2} .2503564{col 41}{space 1}    2.45{col 50}{space 3}0.018{col 58}{space 4} .1100879{col 71}{space 3}  1.11797
{txt}{space 11}urban {c |}{col 18}{res}{space 2} 3.873313{col 30}{space 2} 8.002954{col 41}{space 1}    0.48{col 50}{space 3}0.631{col 58}{space 4} -12.2358{col 71}{space 3} 19.98242
{txt}{space 10}income {c |}{col 18}{res}{space 2} .0426468{col 30}{space 2} .0839216{col 41}{space 1}    0.51{col 50}{space 3}0.614{col 58}{space 4}-.1262785{col 71}{space 3} .2115722
{txt}{space 8}lfullemp {c |}{col 18}{res}{space 2} .2299601{col 30}{space 2} .3744525{col 41}{space 1}    0.61{col 50}{space 3}0.542{col 58}{space 4}-.5237737{col 71}{space 3} .9836939
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-4.346797{col 30}{space 2} 6.501081{col 41}{space 1}   -0.67{col 50}{space 3}0.507{col 58}{space 4}-17.43279{col 71}{space 3}   8.7392
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 14}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}  Absorbed FE{col 15}{c |} Categories{col 28} - Redundant{col 40}  = Num. Coefs{col 55}{c |}
{res}{col 1}{text}{hline 14}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text} state#c.year{col 15}{c |}{space 1}       47{col 28}{space 1}        0{col 40}{result}{space 1}       47{col 54}{text} {col 55}{c |}
{res}{col 1}{text}         year{col 15}{c |}{space 1}       19{col 28}{space 1}        0{col 40}{result}{space 1}       19{col 54}{text}?{col 55}{c |}
{res}{col 1}{text}{hline 14}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table2, tex append keep(divided_governor divided_chamber ideociti urban income  lfullemp ) label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X,  State-Specific Trends, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table2.tex"'"':Table2.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table2.txt", label"':seeout}

{com}. 
. ologit civil_service_reform_ipe divided_governor divided_chamber ideociti urban income  lfullemp i.year  i.state ,   cl(state) 

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -803.7917}  
Iteration 1:{space 3}log pseudolikelihood = {res:-415.05773}  
Iteration 2:{space 3}log pseudolikelihood = {res:-381.30762}  
Iteration 3:{space 3}log pseudolikelihood = {res:-374.35063}  
Iteration 4:{space 3}log pseudolikelihood = {res:-373.49022}  
Iteration 5:{space 3}log pseudolikelihood = {res:-373.27799}  
Iteration 6:{space 3}log pseudolikelihood = {res: -373.2349}  
Iteration 7:{space 3}log pseudolikelihood = {res:-373.22559}  
Iteration 8:{space 3}log pseudolikelihood = {res:-373.22351}  
Iteration 9:{space 3}log pseudolikelihood = {res:-373.22298}  
Iteration 10:{space 2}log pseudolikelihood = {res:-373.22288}  
Iteration 11:{space 2}log pseudolikelihood = {res:-373.22287}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       830
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(38)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-373.22287{txt}{col 49}Pseudo R2{col 67}= {res}    0.5357

{txt}{ralign 90:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}civil_service_reform_ipe{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}divided_governor {c |}{col 26}{res}{space 2} .4389815{col 38}{space 2} .3885719{col 49}{space 1}    1.13{col 58}{space 3}0.259{col 66}{space 4}-.3226055{col 79}{space 3} 1.200568
{txt}{space 9}divided_chamber {c |}{col 26}{res}{space 2}  .769751{col 38}{space 2} .3628493{col 49}{space 1}    2.12{col 58}{space 3}0.034{col 66}{space 4} .0585794{col 79}{space 3} 1.480923
{txt}{space 16}ideociti {c |}{col 26}{res}{space 2} 8.205275{col 38}{space 2} 2.867252{col 49}{space 1}    2.86{col 58}{space 3}0.004{col 66}{space 4} 2.585565{col 79}{space 3} 13.82499
{txt}{space 19}urban {c |}{col 26}{res}{space 2} 46.68882{col 38}{space 2} 29.78577{col 49}{space 1}    1.57{col 58}{space 3}0.117{col 66}{space 4}-11.69021{col 79}{space 3} 105.0679
{txt}{space 18}income {c |}{col 26}{res}{space 2}-.0588954{col 38}{space 2} .4519313{col 49}{space 1}   -0.13{col 58}{space 3}0.896{col 66}{space 4}-.9446645{col 79}{space 3} .8268737
{txt}{space 16}lfullemp {c |}{col 26}{res}{space 2}-2.829657{col 38}{space 2} 4.211904{col 49}{space 1}   -0.67{col 58}{space 3}0.502{col 66}{space 4}-11.08484{col 79}{space 3} 5.425523
{txt}{space 24} {c |}
{space 20}year {c |}
{space 19}1966  {c |}{col 26}{res}{space 2} .3692659{col 38}{space 2} .4132199{col 49}{space 1}    0.89{col 58}{space 3}0.372{col 66}{space 4}-.4406302{col 79}{space 3} 1.179162
{txt}{space 19}1967  {c |}{col 26}{res}{space 2} .5930492{col 38}{space 2} .6658466{col 49}{space 1}    0.89{col 58}{space 3}0.373{col 66}{space 4}-.7119862{col 79}{space 3} 1.898085
{txt}{space 19}1968  {c |}{col 26}{res}{space 2}  .617914{col 38}{space 2} .9880866{col 49}{space 1}    0.63{col 58}{space 3}0.532{col 66}{space 4}  -1.3187{col 79}{space 3} 2.554528
{txt}{space 19}1969  {c |}{col 26}{res}{space 2} 1.147979{col 38}{space 2} 1.090213{col 49}{space 1}    1.05{col 58}{space 3}0.292{col 66}{space 4}-.9887998{col 79}{space 3} 3.284757
{txt}{space 19}1970  {c |}{col 26}{res}{space 2}  1.18614{col 38}{space 2} 1.257625{col 49}{space 1}    0.94{col 58}{space 3}0.346{col 66}{space 4}-1.278759{col 79}{space 3} 3.651039
{txt}{space 19}1971  {c |}{col 26}{res}{space 2} .7165229{col 38}{space 2} 1.404432{col 49}{space 1}    0.51{col 58}{space 3}0.610{col 66}{space 4}-2.036113{col 79}{space 3} 3.469158
{txt}{space 19}1972  {c |}{col 26}{res}{space 2} 1.326026{col 38}{space 2} 1.774171{col 49}{space 1}    0.75{col 58}{space 3}0.455{col 66}{space 4}-2.151285{col 79}{space 3} 4.803337
{txt}{space 19}1973  {c |}{col 26}{res}{space 2} 1.296206{col 38}{space 2} 2.044967{col 49}{space 1}    0.63{col 58}{space 3}0.526{col 66}{space 4}-2.711855{col 79}{space 3} 5.304267
{txt}{space 19}1974  {c |}{col 26}{res}{space 2} 1.525673{col 38}{space 2} 2.130452{col 49}{space 1}    0.72{col 58}{space 3}0.474{col 66}{space 4}-2.649935{col 79}{space 3} 5.701281
{txt}{space 19}1975  {c |}{col 26}{res}{space 2} 1.507216{col 38}{space 2} 2.317841{col 49}{space 1}    0.65{col 58}{space 3}0.516{col 66}{space 4}-3.035669{col 79}{space 3} 6.050101
{txt}{space 19}1976  {c |}{col 26}{res}{space 2} 2.144935{col 38}{space 2} 2.370098{col 49}{space 1}    0.90{col 58}{space 3}0.365{col 66}{space 4}-2.500371{col 79}{space 3} 6.790242
{txt}{space 19}1977  {c |}{col 26}{res}{space 2} 2.251908{col 38}{space 2} 2.543353{col 49}{space 1}    0.89{col 58}{space 3}0.376{col 66}{space 4}-2.732972{col 79}{space 3} 7.236787
{txt}{space 19}1978  {c |}{col 26}{res}{space 2}  2.35452{col 38}{space 2} 2.711382{col 49}{space 1}    0.87{col 58}{space 3}0.385{col 66}{space 4}-2.959691{col 79}{space 3} 7.668732
{txt}{space 19}1979  {c |}{col 26}{res}{space 2} 2.247649{col 38}{space 2} 2.846677{col 49}{space 1}    0.79{col 58}{space 3}0.430{col 66}{space 4}-3.331735{col 79}{space 3} 7.827033
{txt}{space 19}1980  {c |}{col 26}{res}{space 2} 2.284431{col 38}{space 2} 2.788307{col 49}{space 1}    0.82{col 58}{space 3}0.413{col 66}{space 4}-3.180552{col 79}{space 3} 7.749413
{txt}{space 19}1981  {c |}{col 26}{res}{space 2} 2.462381{col 38}{space 2} 2.759621{col 49}{space 1}    0.89{col 58}{space 3}0.372{col 66}{space 4}-2.946377{col 79}{space 3} 7.871139
{txt}{space 19}1982  {c |}{col 26}{res}{space 2} 1.776091{col 38}{space 2} 2.716278{col 49}{space 1}    0.65{col 58}{space 3}0.513{col 66}{space 4}-3.547716{col 79}{space 3} 7.099898
{txt}{space 19}1983  {c |}{col 26}{res}{space 2} 1.743638{col 38}{space 2} 2.693514{col 49}{space 1}    0.65{col 58}{space 3}0.517{col 66}{space 4}-3.535552{col 79}{space 3} 7.022828
{txt}{space 24} {c |}
{space 19}state {c |}
{space 21}AR  {c |}{col 26}{res}{space 2}-15.47661{col 38}{space 2} 2.782631{col 49}{space 1}   -5.56{col 58}{space 3}0.000{col 66}{space 4}-20.93047{col 79}{space 3}-10.02276
{txt}{space 21}AZ  {c |}{col 26}{res}{space 2}-30.04316{col 38}{space 2} 7.448173{col 49}{space 1}   -4.03{col 58}{space 3}0.000{col 66}{space 4}-44.64131{col 79}{space 3}  -15.445
{txt}{space 21}CA  {c |}{col 26}{res}{space 2}-31.50531{col 38}{space 2} 9.331056{col 49}{space 1}   -3.38{col 58}{space 3}0.001{col 66}{space 4}-49.79385{col 79}{space 3}-13.21678
{txt}{space 21}CO  {c |}{col 26}{res}{space 2}-32.45887{col 38}{space 2}  6.15934{col 49}{space 1}   -5.27{col 58}{space 3}0.000{col 66}{space 4}-44.53096{col 79}{space 3}-20.38679
{txt}{space 21}CT  {c |}{col 26}{res}{space 2}-32.12214{col 38}{space 2} 5.834335{col 49}{space 1}   -5.51{col 58}{space 3}0.000{col 66}{space 4}-43.55723{col 79}{space 3}-20.68705
{txt}{space 21}DE  {c |}{col 26}{res}{space 2}-32.23663{col 38}{space 2} 6.954453{col 49}{space 1}   -4.64{col 58}{space 3}0.000{col 66}{space 4}-45.86711{col 79}{space 3}-18.60615
{txt}{space 21}FL  {c |}{col 26}{res}{space 2}-26.52865{col 38}{space 2} 6.348345{col 49}{space 1}   -4.18{col 58}{space 3}0.000{col 66}{space 4}-38.97118{col 79}{space 3}-14.08612
{txt}{space 21}GA  {c |}{col 26}{res}{space 2}-17.86815{col 38}{space 2} 1.746621{col 49}{space 1}  -10.23{col 58}{space 3}0.000{col 66}{space 4}-21.29146{col 79}{space 3}-14.44483
{txt}{space 21}IA  {c |}{col 26}{res}{space 2}-18.10487{col 38}{space 2} 2.032738{col 49}{space 1}   -8.91{col 58}{space 3}0.000{col 66}{space 4}-22.08896{col 79}{space 3}-14.12077
{txt}{space 21}ID  {c |}{col 26}{res}{space 2}-19.79237{col 38}{space 2} 5.190904{col 49}{space 1}   -3.81{col 58}{space 3}0.000{col 66}{space 4}-29.96636{col 79}{space 3}-9.618388
{txt}{space 21}IL  {c |}{col 26}{res}{space 2}-31.84699{col 38}{space 2} 6.740917{col 49}{space 1}   -4.72{col 58}{space 3}0.000{col 66}{space 4}-45.05894{col 79}{space 3}-18.63504
{txt}{space 21}IN  {c |}{col 26}{res}{space 2}-22.56583{col 38}{space 2} 2.083891{col 49}{space 1}  -10.83{col 58}{space 3}0.000{col 66}{space 4}-26.65018{col 79}{space 3}-18.48148
{txt}{space 21}KS  {c |}{col 26}{res}{space 2} -6.28666{col 38}{space 2} 2.910369{col 49}{space 1}   -2.16{col 58}{space 3}0.031{col 66}{space 4}-11.99088{col 79}{space 3}-.5824421
{txt}{space 21}KY  {c |}{col 26}{res}{space 2}-18.28643{col 38}{space 2} 2.888443{col 49}{space 1}   -6.33{col 58}{space 3}0.000{col 66}{space 4}-23.94768{col 79}{space 3}-12.62519
{txt}{space 21}LA  {c |}{col 26}{res}{space 2}-3.148853{col 38}{space 2} 2.768598{col 49}{space 1}   -1.14{col 58}{space 3}0.255{col 66}{space 4}-8.575205{col 79}{space 3} 2.277499
{txt}{space 21}MA  {c |}{col 26}{res}{space 2}-15.61106{col 38}{space 2} 7.034537{col 49}{space 1}   -2.22{col 58}{space 3}0.026{col 66}{space 4} -29.3985{col 79}{space 3}-1.823619
{txt}{space 21}MD  {c |}{col 26}{res}{space 2}-31.53128{col 38}{space 2} 5.334068{col 49}{space 1}   -5.91{col 58}{space 3}0.000{col 66}{space 4}-41.98587{col 79}{space 3} -21.0767
{txt}{space 21}ME  {c |}{col 26}{res}{space 2}-19.66144{col 38}{space 2} 4.615062{col 49}{space 1}   -4.26{col 58}{space 3}0.000{col 66}{space 4}-28.70679{col 79}{space 3}-10.61608
{txt}{space 21}MI  {c |}{col 26}{res}{space 2}-7.820214{col 38}{space 2} 4.464078{col 49}{space 1}   -1.75{col 58}{space 3}0.080{col 66}{space 4}-16.56965{col 79}{space 3} .9292183
{txt}{space 21}MN  {c |}{col 26}{res}{space 2}-24.91195{col 38}{space 2} 2.643454{col 49}{space 1}   -9.42{col 58}{space 3}0.000{col 66}{space 4}-30.09302{col 79}{space 3}-19.73087
{txt}{space 21}MO  {c |}{col 26}{res}{space 2}-24.30548{col 38}{space 2}    2.963{col 49}{space 1}   -8.20{col 58}{space 3}0.000{col 66}{space 4}-30.11285{col 79}{space 3}-18.49811
{txt}{space 21}MS  {c |}{col 26}{res}{space 2}-17.37293{col 38}{space 2}  3.68556{col 49}{space 1}   -4.71{col 58}{space 3}0.000{col 66}{space 4}-24.59649{col 79}{space 3}-10.14936
{txt}{space 21}MT  {c |}{col 26}{res}{space 2} -24.8711{col 38}{space 2} 5.051665{col 49}{space 1}   -4.92{col 58}{space 3}0.000{col 66}{space 4}-34.77218{col 79}{space 3}-14.97002
{txt}{space 21}NC  {c |}{col 26}{res}{space 2} 7.743701{col 38}{space 2} 5.281113{col 49}{space 1}    1.47{col 58}{space 3}0.143{col 66}{space 4} -2.60709{col 79}{space 3} 18.09449
{txt}{space 21}ND  {c |}{col 26}{res}{space 2}-22.43985{col 38}{space 2} 6.345374{col 49}{space 1}   -3.54{col 58}{space 3}0.000{col 66}{space 4}-34.87655{col 79}{space 3}-10.00314
{txt}{space 21}NH  {c |}{col 26}{res}{space 2}-18.73988{col 38}{space 2} 5.762455{col 49}{space 1}   -3.25{col 58}{space 3}0.001{col 66}{space 4}-30.03409{col 79}{space 3}-7.445678
{txt}{space 21}NJ  {c |}{col 26}{res}{space 2}-36.43769{col 38}{space 2} 8.228101{col 49}{space 1}   -4.43{col 58}{space 3}0.000{col 66}{space 4}-52.56447{col 79}{space 3}-20.31091
{txt}{space 21}NM  {c |}{col 26}{res}{space 2}-25.95559{col 38}{space 2} 5.084481{col 49}{space 1}   -5.10{col 58}{space 3}0.000{col 66}{space 4}-35.92099{col 79}{space 3}-15.99019
{txt}{space 21}NV  {c |}{col 26}{res}{space 2}-15.47595{col 38}{space 2} 10.62863{col 49}{space 1}   -1.46{col 58}{space 3}0.145{col 66}{space 4}-36.30767{col 79}{space 3} 5.355777
{txt}{space 21}NY  {c |}{col 26}{res}{space 2}-32.21631{col 38}{space 2} 8.221579{col 49}{space 1}   -3.92{col 58}{space 3}0.000{col 66}{space 4}-48.33031{col 79}{space 3}-16.10231
{txt}{space 21}OH  {c |}{col 26}{res}{space 2} -26.2185{col 38}{space 2} 4.728313{col 49}{space 1}   -5.55{col 58}{space 3}0.000{col 66}{space 4}-35.48582{col 79}{space 3}-16.95118
{txt}{space 21}OK  {c |}{col 26}{res}{space 2}-5.208561{col 38}{space 2} 2.764522{col 49}{space 1}   -1.88{col 58}{space 3}0.060{col 66}{space 4}-10.62692{col 79}{space 3} .2098025
{txt}{space 21}OR  {c |}{col 26}{res}{space 2}-27.01793{col 38}{space 2} 3.254055{col 49}{space 1}   -8.30{col 58}{space 3}0.000{col 66}{space 4}-33.39576{col 79}{space 3} -20.6401
{txt}{space 21}PA  {c |}{col 26}{res}{space 2}-24.18665{col 38}{space 2} 5.097107{col 49}{space 1}   -4.75{col 58}{space 3}0.000{col 66}{space 4} -34.1768{col 79}{space 3}-14.19651
{txt}{space 21}RI  {c |}{col 26}{res}{space 2}-37.36551{col 38}{space 2} 10.19689{col 49}{space 1}   -3.66{col 58}{space 3}0.000{col 66}{space 4}-57.35105{col 79}{space 3}-17.37996
{txt}{space 21}SC  {c |}{col 26}{res}{space 2}-13.31719{col 38}{space 2} 2.780165{col 49}{space 1}   -4.79{col 58}{space 3}0.000{col 66}{space 4}-18.76621{col 79}{space 3}-7.868163
{txt}{space 21}SD  {c |}{col 26}{res}{space 2}-22.21833{col 38}{space 2} 6.256866{col 49}{space 1}   -3.55{col 58}{space 3}0.000{col 66}{space 4}-34.48156{col 79}{space 3}-9.955096
{txt}{space 21}TN  {c |}{col 26}{res}{space 2}-21.40573{col 38}{space 2} 1.547423{col 49}{space 1}  -13.83{col 58}{space 3}0.000{col 66}{space 4}-24.43862{col 79}{space 3}-18.37283
{txt}{space 21}TX  {c |}{col 26}{res}{space 2}-54.39551{col 38}{space 2} 6.385359{col 49}{space 1}   -8.52{col 58}{space 3}0.000{col 66}{space 4}-66.91058{col 79}{space 3}-41.88044
{txt}{space 21}UT  {c |}{col 26}{res}{space 2}-29.21677{col 38}{space 2}  8.06204{col 49}{space 1}   -3.62{col 58}{space 3}0.000{col 66}{space 4}-45.01808{col 79}{space 3}-13.41547
{txt}{space 21}VA  {c |}{col 26}{res}{space 2} -20.8568{col 38}{space 2} 2.584959{col 49}{space 1}   -8.07{col 58}{space 3}0.000{col 66}{space 4}-25.92322{col 79}{space 3}-15.79037
{txt}{space 21}VT  {c |}{col 26}{res}{space 2}-14.69408{col 38}{space 2} 8.597378{col 49}{space 1}   -1.71{col 58}{space 3}0.087{col 66}{space 4}-31.54463{col 79}{space 3} 2.156468
{txt}{space 21}WA  {c |}{col 26}{res}{space 2}-29.84326{col 38}{space 2} 4.092009{col 49}{space 1}   -7.29{col 58}{space 3}0.000{col 66}{space 4}-37.86345{col 79}{space 3}-21.82307
{txt}{space 21}WI  {c |}{col 26}{res}{space 2}-21.49263{col 38}{space 2} 2.324466{col 49}{space 1}   -9.25{col 58}{space 3}0.000{col 66}{space 4} -26.0485{col 79}{space 3}-16.93676
{txt}{space 21}WV  {c |}{col 26}{res}{space 2}-41.19302{col 38}{space 2} 6.338427{col 49}{space 1}   -6.50{col 58}{space 3}0.000{col 66}{space 4} -53.6161{col 79}{space 3}-28.76993
{txt}{space 21}WY  {c |}{col 26}{res}{space 2}-27.37338{col 38}{space 2} 7.751202{col 49}{space 1}   -3.53{col 58}{space 3}0.000{col 66}{space 4}-42.56546{col 79}{space 3}-12.18131
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}/cut1 {c |}{col 26}{res}{space 2}-22.67551{col 38}{space 2} 40.87742{col 66}{space 4}-102.7938{col 79}{space 3} 57.44276
{txt}{space 19}/cut2 {c |}{col 26}{res}{space 2}-17.94362{col 38}{space 2} 40.90587{col 66}{space 4}-98.11764{col 79}{space 3} 62.23041
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 188 observations completely determined.{txt}  Standard errors questionable.{p_end}

{com}. outreg2 using Table2, tex append keep(divided_governor divided_chamber ideociti urban income  lfullemp ) label   ctitle(Merit IPE - Ologit)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table2.tex"'"':Table2.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table2.txt", label"':seeout}

{com}. 
. reghdfe civil_service_reform divided_governor divided_chamber ideociti urban income  lfullemp, a(state year )     cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 2 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       893
{txt}Absorbing 2 HDFE groups{col 51}F({res}   6{txt},{res}     46{txt}){col 67}= {res}      3.01
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0145
{txt}{col 51}R-squared{col 67}= {res}    0.7074
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6821
{txt}{col 51}Within R-sq.{col 67}= {res}    0.1331
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.1739

{txt}{ralign 82:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}civil_service_~m{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_governor {c |}{col 18}{res}{space 2}-.0087826{col 30}{space 2} .0193161{col 41}{space 1}   -0.45{col 50}{space 3}0.651{col 58}{space 4} -.047664{col 71}{space 3} .0300988
{txt}{space 1}divided_chamber {c |}{col 18}{res}{space 2} .0535352{col 30}{space 2} .0187707{col 41}{space 1}    2.85{col 50}{space 3}0.006{col 58}{space 4} .0157517{col 71}{space 3} .0913187
{txt}{space 8}ideociti {c |}{col 18}{res}{space 2} .2679756{col 30}{space 2} .1838548{col 41}{space 1}    1.46{col 50}{space 3}0.152{col 58}{space 4} -.102105{col 71}{space 3} .6380562
{txt}{space 11}urban {c |}{col 18}{res}{space 2} 5.724482{col 30}{space 2} 1.801538{col 41}{space 1}    3.18{col 50}{space 3}0.003{col 58}{space 4} 2.098173{col 71}{space 3} 9.350791
{txt}{space 10}income {c |}{col 18}{res}{space 2}-.0132743{col 30}{space 2} .0276364{col 41}{space 1}   -0.48{col 50}{space 3}0.633{col 58}{space 4}-.0689035{col 71}{space 3} .0423549
{txt}{space 8}lfullemp {c |}{col 18}{res}{space 2}-.4055942{col 30}{space 2} .2507077{col 41}{space 1}   -1.62{col 50}{space 3}0.113{col 58}{space 4}-.9102427{col 71}{space 3} .0990543
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.384459{col 30}{space 2} 2.069579{col 41}{space 1}    0.67{col 50}{space 3}0.507{col 58}{space 4}-2.781387{col 71}{space 3} 5.550305
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table2, tex append keep(divided_governor divided_chamber ideociti urban income  lfullemp ) label   ctitle(Merit)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table2.tex"'"':Table2.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table2.txt", label"':seeout}

{com}. 
. *effect on second category stronger for divided chambers
. 
. quietly ologit civil_service_reform_ipe divided_governor divided_chamber ideociti urban income  lfullemp i.year  i.state ,   cl(state)
{txt}
{com}. margins, predict(outcome(2)) at( divided_governor =0) atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}       830
{txt}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(civil_service_reform_ipe==2), predict(outcome(2))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:divided_go~r}{space 4}{txt:=} {space 10}0}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:divided_ch~r}{space 4}{txt:=} {space 3}.1542169 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:ideociti}{space 8}{txt:=} {space 3}.4327353 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:urban}{space 11}{txt:=} {space 4}.657417 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:income}{space 10}{txt:=} {space 3}10.61175 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:lfullemp}{space 8}{txt:=} {space 3}10.47336 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1965.year}{space 7}{txt:=} {space 3}.0554217 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1966.year}{space 7}{txt:=} {space 3}.0542169 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1967.year}{space 7}{txt:=} {space 3}.0554217 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1968.year}{space 7}{txt:=} {space 3}.0506024 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1969.year}{space 7}{txt:=} {space 3}.0566265 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1970.year}{space 7}{txt:=} {space 4}.053012 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1971.year}{space 7}{txt:=} {space 3}.0566265 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1972.year}{space 7}{txt:=} {space 3}.0481928 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1973.year}{space 7}{txt:=} {space 3}.0566265 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1974.year}{space 7}{txt:=} {space 3}.0506024 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1975.year}{space 7}{txt:=} {space 3}.0554217 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1976.year}{space 7}{txt:=} {space 3}.0506024 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1977.year}{space 7}{txt:=} {space 3}.0554217 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1978.year}{space 7}{txt:=} {space 4}.046988 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1979.year}{space 7}{txt:=} {space 4}.046988 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1980.year}{space 7}{txt:=} {space 3}.0542169 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1981.year}{space 7}{txt:=} {space 4}.046988 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1982.year}{space 7}{txt:=} {space 3}.0542169 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1983.year}{space 7}{txt:=} {space 3}.0518072 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.state}{space 9}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:3.state}{space 9}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:4.state}{space 9}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:5.state}{space 9}{txt:=} {space 3}.0168675 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:6.state}{space 9}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:7.state}{space 9}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:8.state}{space 9}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:9.state}{space 9}{txt:=} {space 3}.0168675 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:10.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:12.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:13.state}{space 8}{txt:=} {space 3}.0180723 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:14.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:15.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:16.state}{space 8}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:17.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:18.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:19.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:20.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:21.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:22.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:23.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:24.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:25.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:26.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:27.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:28.state}{space 8}{txt:=} {space 3}.0192771 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:30.state}{space 8}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:31.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:32.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:33.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:34.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:35.state}{space 8}{txt:=} {space 3}.0156627 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:36.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:37.state}{space 8}{txt:=} {space 3}.0180723 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:38.state}{space 8}{txt:=} {space 3}.0156627 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:39.state}{space 8}{txt:=} {space 3}.0192771 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:40.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:41.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:42.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:43.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:44.state}{space 8}{txt:=} {space 3}.0192771 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:45.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:46.state}{space 8}{txt:=} {space 3}.0180723 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:47.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:48.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:49.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:50.state}{space 8}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .7387249{col 26}{space 2} .0607292{col 37}{space 1}   12.16{col 46}{space 3}0.000{col 54}{space 4} .6196978{col 67}{space 3}  .857752
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. quietly ologit civil_service_reform_ipe divided_governor divided_chamber ideociti urban income  lfullemp i.year  i.state ,   cl(state)
{txt}
{com}. margins, predict(outcome(2)) at( divided_governor =1) atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}       830
{txt}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(civil_service_reform_ipe==2), predict(outcome(2))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:divided_go~r}{space 4}{txt:=} {space 10}1}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:divided_ch~r}{space 4}{txt:=} {space 3}.1542169 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:ideociti}{space 8}{txt:=} {space 3}.4327353 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:urban}{space 11}{txt:=} {space 4}.657417 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:income}{space 10}{txt:=} {space 3}10.61175 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:lfullemp}{space 8}{txt:=} {space 3}10.47336 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1965.year}{space 7}{txt:=} {space 3}.0554217 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1966.year}{space 7}{txt:=} {space 3}.0542169 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1967.year}{space 7}{txt:=} {space 3}.0554217 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1968.year}{space 7}{txt:=} {space 3}.0506024 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1969.year}{space 7}{txt:=} {space 3}.0566265 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1970.year}{space 7}{txt:=} {space 4}.053012 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1971.year}{space 7}{txt:=} {space 3}.0566265 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1972.year}{space 7}{txt:=} {space 3}.0481928 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1973.year}{space 7}{txt:=} {space 3}.0566265 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1974.year}{space 7}{txt:=} {space 3}.0506024 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1975.year}{space 7}{txt:=} {space 3}.0554217 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1976.year}{space 7}{txt:=} {space 3}.0506024 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1977.year}{space 7}{txt:=} {space 3}.0554217 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1978.year}{space 7}{txt:=} {space 4}.046988 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1979.year}{space 7}{txt:=} {space 4}.046988 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1980.year}{space 7}{txt:=} {space 3}.0542169 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1981.year}{space 7}{txt:=} {space 4}.046988 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1982.year}{space 7}{txt:=} {space 3}.0542169 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:1983.year}{space 7}{txt:=} {space 3}.0518072 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:2.state}{space 9}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:3.state}{space 9}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:4.state}{space 9}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:5.state}{space 9}{txt:=} {space 3}.0168675 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:6.state}{space 9}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:7.state}{space 9}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:8.state}{space 9}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:9.state}{space 9}{txt:=} {space 3}.0168675 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:10.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:12.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:13.state}{space 8}{txt:=} {space 3}.0180723 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:14.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:15.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:16.state}{space 8}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:17.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:18.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:19.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:20.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:21.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:22.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:23.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:24.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:25.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:26.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:27.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:28.state}{space 8}{txt:=} {space 3}.0192771 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:30.state}{space 8}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:31.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:32.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:33.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:34.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:35.state}{space 8}{txt:=} {space 3}.0156627 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:36.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:37.state}{space 8}{txt:=} {space 3}.0180723 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:38.state}{space 8}{txt:=} {space 3}.0156627 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:39.state}{space 8}{txt:=} {space 3}.0192771 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:40.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:41.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:42.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:43.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:44.state}{space 8}{txt:=} {space 3}.0192771 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:45.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:46.state}{space 8}{txt:=} {space 3}.0180723 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:47.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:48.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:49.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:50.state}{space 8}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .8143207{col 26}{space 2} .0562519{col 37}{space 1}   14.48{col 46}{space 3}0.000{col 54}{space 4} .7040689{col 67}{space 3} .9245724
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. quietly ologit civil_service_reform_ipe divided_governor divided_chamber ideociti urban income  lfullemp i.year  i.state ,   cl(state)
{txt}
{com}. margins, predict(outcome(2)) at( divided_chamber =0) atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}       830
{txt}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(civil_service_reform_ipe==2), predict(outcome(2))}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:at}:{space 1}{res:{txt:divided_go~r}{space 4}{txt:=} {space 3}.3036145 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:divided_ch~r}{space 4}{txt:=} {space 10}0}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:ideociti}{space 8}{txt:=} {space 3}.4327353 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:urban}{space 11}{txt:=} {space 4}.657417 {txt:(mean)}}{p_end}
{p2colreset}{...}
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{txt}{p2colset 1 14 16 2}{...}
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{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .7415277{col 26}{space 2} .0516757{col 37}{space 1}   14.35{col 46}{space 3}0.000{col 54}{space 4} .6402453{col 67}{space 3} .8428102
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. quietly ologit civil_service_reform_ipe divided_governor divided_chamber ideociti urban income  lfullemp i.year  i.state ,   cl(state)
{txt}
{com}. margins, predict(outcome(2)) at( divided_chamber =1) atmeans post
{res}
{txt}Adjusted predictions{col 49}Number of obs{col 67}= {res}       830
{txt}Model VCE{col 14}: {res}Robust

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{p2col: }{space 2}{res:{txt:19.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
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{p2col: }{space 2}{res:{txt:24.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:25.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:26.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:27.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:28.state}{space 8}{txt:=} {space 3}.0192771 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:30.state}{space 8}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:31.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:32.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:33.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:34.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:35.state}{space 8}{txt:=} {space 3}.0156627 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:36.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:37.state}{space 8}{txt:=} {space 3}.0180723 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:38.state}{space 8}{txt:=} {space 3}.0156627 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:39.state}{space 8}{txt:=} {space 3}.0192771 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:40.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:41.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:42.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:43.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:44.state}{space 8}{txt:=} {space 3}.0192771 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:45.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:46.state}{space 8}{txt:=} {space 3}.0180723 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:47.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:48.state}{space 8}{txt:=} {space 3}.0216867 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:49.state}{space 8}{txt:=} {space 3}.0228916 {txt:(mean)}}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col: }{space 2}{res:{txt:50.state}{space 8}{txt:=} {space 3}.0204819 {txt:(mean)}}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}_cons {c |}{col 14}{res}{space 2} .8610065{col 26}{space 2} .0483434{col 37}{space 1}   17.81{col 46}{space 3}0.000{col 54}{space 4} .7662553{col 67}{space 3} .9557578
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *// Figure 1
. 
. grstyle init
{res}{txt}
{com}. grstyle set plain, horizontal grid
{txt}
{com}. 
. eststo clear
{txt}
{com}. eststo: reghdfe civil_service_reform_ipe divided_either , a(state year  state##c.year )    cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 3 HDFE groups{col 51}F({res}   1{txt},{res}     46{txt}){col 67}= {res}      2.31
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.1352
{txt}{col 51}R-squared{col 67}= {res}    0.8355
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7962
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0069
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.3053

{txt}{ralign 80:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}civil_servic~e{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_either {c |}{col 16}{res}{space 2} .0596158{col 28}{space 2} .0392066{col 39}{space 1}    1.52{col 48}{space 3}0.135{col 56}{space 4}-.0193029{col 69}{space 3} .1385345
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 1.323308{col 28}{space 2}   .01795{col 39}{space 1}   73.72{col 48}{space 3}0.000{col 56}{space 4} 1.287177{col 69}{space 3}  1.35944
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 14}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}  Absorbed FE{col 15}{c |} Categories{col 28} - Redundant{col 40}  = Num. Coefs{col 55}{c |}
{res}{col 1}{text}{hline 14}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text}         year{col 15}{c |}{space 1}       19{col 28}{space 1}        0{col 40}{result}{space 1}       19{col 54}{text} {col 55}{c |}
{res}{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text} state#c.year{col 15}{c |}{space 1}       47{col 28}{space 1}        0{col 40}{result}{space 1}       47{col 54}{text}?{col 55}{c |}
{res}{col 1}{text}{hline 14}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}({res}est1{txt} stored)

{com}. eststo: reghdfe civil_service_reform_ipe true_divided_gov_a, a(state year state##c.year)   cl(state) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 3 HDFE groups{col 51}F({res}   1{txt},{res}     46{txt}){col 67}= {res}      3.45
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0697
{txt}{col 51}R-squared{col 67}= {res}    0.8362
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7970
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0110
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.3046

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_a {c |}{col 20}{res}{space 2} .0846441{col 32}{space 2} .0455737{col 43}{space 1}    1.86{col 52}{space 3}0.070{col 60}{space 4}-.0070911{col 73}{space 3} .1763793
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.321946{col 32}{space 2} .0154292{col 43}{space 1}   85.68{col 52}{space 3}0.000{col 60}{space 4} 1.290888{col 73}{space 3} 1.353003
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 14}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}  Absorbed FE{col 15}{c |} Categories{col 28} - Redundant{col 40}  = Num. Coefs{col 55}{c |}
{res}{col 1}{text}{hline 14}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text}         year{col 15}{c |}{space 1}       19{col 28}{space 1}        0{col 40}{result}{space 1}       19{col 54}{text} {col 55}{c |}
{res}{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text} state#c.year{col 15}{c |}{space 1}       47{col 28}{space 1}        0{col 40}{result}{space 1}       47{col 54}{text}?{col 55}{c |}
{res}{col 1}{text}{hline 14}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}({res}est2{txt} stored)

{com}. eststo: reghdfe civil_service_reform_ipe divided_governor divided_chamber , a(state year state##c.year)   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 3 HDFE groups{col 51}F({res}   2{txt},{res}     46{txt}){col 67}= {res}      1.72
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.1900
{txt}{col 51}R-squared{col 67}= {res}    0.8356
{txt}{col 51}Adj R-squared{col 67}= {res}    0.7960
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0074
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.3054

{txt}{ralign 82:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}civil_service_~e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_governor {c |}{col 18}{res}{space 2} .0514136{col 30}{space 2} .0467491{col 41}{space 1}    1.10{col 50}{space 3}0.277{col 58}{space 4}-.0426876{col 71}{space 3} .1455147
{txt}{space 1}divided_chamber {c |}{col 18}{res}{space 2} .0749058{col 30}{space 2} .0406944{col 41}{space 1}    1.84{col 50}{space 3}0.072{col 58}{space 4}-.0070079{col 71}{space 3} .1568194
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.323441{col 30}{space 2} .0180916{col 41}{space 1}   73.15{col 50}{space 3}0.000{col 58}{space 4} 1.287024{col 71}{space 3} 1.359857
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 14}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}  Absorbed FE{col 15}{c |} Categories{col 28} - Redundant{col 40}  = Num. Coefs{col 55}{c |}
{res}{col 1}{text}{hline 14}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text}         year{col 15}{c |}{space 1}       19{col 28}{space 1}        0{col 40}{result}{space 1}       19{col 54}{text} {col 55}{c |}
{res}{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text} state#c.year{col 15}{c |}{space 1}       47{col 28}{space 1}        0{col 40}{result}{space 1}       47{col 54}{text}?{col 55}{c |}
{res}{col 1}{text}{hline 14}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}({res}est3{txt} stored)

{com}. 
. 
. coefplot est1 est2 est3, drop(_cons) xline(0, lpattern(dash) lcolor(gray)) ci(90) xtitle("Effect on Probability of Civil Service Reform") nokey mlabsize(medium) ylabel(.) mlabels(divided_either = 2 "Divided Any" true_divided_gov_a=2 "Divided Government Veto" divided_governor = 2 "Divided Governor" divided_chamber = 2 "Divided Chamber")
{res}{p 0 4 2}
{txt}(note:  named style
+ not found in class
symbol,  default attributes used)
{p_end}
{res}{txt}
{com}. 
. graph export main-coefplot.pdf, replace
{txt}(file main-coefplot.pdf written in PDF format)

{com}. 
. 
. * results hold when dropping southern states
. 
. reghdfe civil_service_reform_ipe  divided_either if !southern  , a(state year )    cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       515
{txt}Absorbing 2 HDFE groups{col 51}F({res}   1{txt},{res}     29{txt}){col 67}= {res}      7.19
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0119
{txt}{col 51}R-squared{col 67}= {res}    0.5059
{txt}{col 51}Adj R-squared{col 67}= {res}    0.4539
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0283
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        30{txt}{col 51}Root MSE{col 67}= {res}    0.4560

{txt}{ralign 80:(Std. Err. adjusted for {res:30} clusters in state)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}civil_servic~e{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_either {c |}{col 16}{res}{space 2} .1680821{col 28}{space 2} .0626632{col 39}{space 1}    2.68{col 48}{space 3}0.012{col 56}{space 4} .0399215{col 69}{space 3} .2962427
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 1.326695{col 28}{space 2} .0360161{col 39}{space 1}   36.84{col 48}{space 3}0.000{col 56}{space 4} 1.253033{col 69}{space 3} 1.400356
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       30{col 27}{space 1}       30{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. *********************************************************************************************
. *Replication code: Appendix******************************************************************
. *********************************************************************************************
. *\Table a1
. 
. outreg2 using table1a, tex replace sum(log) label keep(civil_service_reform civil_service_reform_ipe ipe simple_divided_gov true_divided_gov_a divided_governor true_divided_gov_e divided_either divided_chamber sen_gov_share hs_gov_share dem_gov_share divided_either  ideociti  urban income  lfullemp)

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 7}state {c |}{res}        950        25.5    14.43847          1         50
{txt}{space 8}year {c |}{res}        950        1974    5.480111       1965       1983
{txt}civil_serv~m {c |}{res}        950    .8894737    .3137098          0          1
{txt}{space 4}ideociti {c |}{res}        912    .4319822    .1748118   .0096254   .8687366
{txt}{space 6}income {c |}{res}        912    10.67549     1.88923   5.297487   15.79997
{txt}{hline 13}{c +}{hline 57}
{space 9}ipe {c |}{res}        849    .4546525    .4982329          0          1
{txt}{space 7}urban {c |}{res}        912    .6591878    .1429231   .3212924   .9170051
{txt}{space 4}lfullemp {c |}{res}        912    10.46766    .8456217   8.434464   12.39937
{txt}simple_div~v {c |}{res}        931    .2996778     .458363          0          1
{txt}true_divid~a {c |}{res}        931    .3447905    .4755554          0          1
{txt}{hline 13}{c +}{hline 57}
true_divid~e {c |}{res}        931    .3609023    .4805204          0          1
{txt}civil_serv~e {c |}{res}        849    1.330978    .6850796          0          2
{txt}divided_go~r {c |}{res}        931    .2996778     .458363          0          1
{txt}divided_ch~r {c |}{res}        950    .1547368    .3618441          0          1
{txt}divided_ei~r {c |}{res}        931    .4575725    .4984644          0          1
{txt}{hline 13}{c +}{hline 57}
sen_gov_sh~e {c |}{res}        931    57.26712    23.62294          0        100
{txt}hs_gov_share {c |}{res}        931    57.13488    22.68642          3        100
{txt}dem_gov_sh~e {c |}{res}        950    6.431006    29.73019       -100        100
{txt}{space 4}southern {c |}{res}        950         .34    .4739583          0          1
{txt}{space 3}_est_est1 {c |}{res}        950    .8736842    .3323799          0          1
{txt}{hline 13}{c +}{hline 57}
{space 3}_est_est2 {c |}{res}        950    .8736842    .3323799          0          1
{txt}{space 3}_est_est3 {c |}{res}        950    .8736842    .3323799          0          1


{txt}{stata `"shellout using `"table1a.tex"'"':table1a.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "table1a.txt", label"':seeout}

{com}. 
. 
. *\Table a2-a4
. 
. foreach x in simple_divided_gov true_divided_gov_a true_divided_gov_e   {c -(}
{txt}  2{com}. 
. areg civil_service_reform_ipe `x', a(state)   cl(state) 
{txt}  3{com}. outreg2 using Table_a`x', tex replace keep(`x') label   ctitle(Merit IPE)    addtext(State FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{txt}  4{com}. areg civil_service_reform_ipe `x' i.year, a(state)   cl(state) 
{txt}  5{com}. outreg2 using Table_a`x', tex append keep(`x') label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{txt}  6{com}. areg civil_service_reform_ipe `x' ideociti urban income  lfullemp i.year i.state#c.year, a(state)   cl(state) 
{txt}  7{com}. outreg2 using Table_a`x', tex append keep(`x' ideociti urban income  lfullemp) label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X, State-Specific Trends, X, Controls, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{txt}  8{com}. ologit civil_service_reform_ipe `x' ideociti urban income  lfullemp i.year  i.state,   cl(state) 
{txt}  9{com}. outreg2 using Table_a`x', tex append keep(`x' ideociti urban income  lfullemp) label   ctitle(Merit IPE - Ologit)    addtext(State FE, X, Time FE, X, Controls, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{txt} 10{com}. areg civil_service_reform `x' ideociti urban income  lfullemp i.year i.state#c.year, a(state)   cl(state)
{txt} 11{com}. outreg2 using Table_a`x', tex append keep(`x' ideociti urban income  lfullemp) label   ctitle(Merit)    addtext(State FE, X, Time FE, X,State-Specific Trends, X,  Controls, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{txt} 12{com}. {c )-}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       830
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}F({res}   1{txt},{res}     46{txt}){col 67}= {res}      2.73
{txt}{col 49}Prob > F{col 67}= {res}    0.1053
{txt}{col 49}R-squared{col 67}= {res}    0.6056
{txt}{col 49}Adj R-squared{col 67}= {res}    0.5819
{txt}{col 49}Root MSE{col 67}= {res}    0.4372

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
simple_divided_gov {c |}{col 20}{res}{space 2} .0862357{col 32}{space 2} .0521868{col 43}{space 1}    1.65{col 52}{space 3}0.105{col 60}{space 4}-.0188109{col 73}{space 3} .1912823
{txt}{space 13}_cons {c |}{col 20}{res}{space 2}  1.32442{col 32}{space 2} .0158447{col 43}{space 1}   83.59{col 52}{space 3}0.000{col 60}{space 4} 1.292526{col 73}{space 3} 1.356314
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{stata `"shellout using `"Table_asimple_divided_gov.tex"'"':Table_asimple_divided_gov.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_asimple_divided_gov.txt", label"':seeout}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       830
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}F({res}  19{txt},{res}     46{txt}){col 67}= {res}      2.01
{txt}{col 49}Prob > F{col 67}= {res}    0.0275
{txt}{col 49}R-squared{col 67}= {res}    0.6288
{txt}{col 49}Adj R-squared{col 67}= {res}    0.5972
{txt}{col 49}Root MSE{col 67}= {res}    0.4291

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
simple_divided_gov {c |}{col 20}{res}{space 2} .0815114{col 32}{space 2} .0605906{col 43}{space 1}    1.35{col 52}{space 3}0.185{col 60}{space 4}-.0404511{col 73}{space 3} .2034739
{txt}{space 18} {c |}
{space 14}year {c |}
{space 13}1966  {c |}{col 20}{res}{space 2} .0303308{col 32}{space 2} .0361828{col 43}{space 1}    0.84{col 52}{space 3}0.406{col 60}{space 4}-.0425014{col 73}{space 3}  .103163
{txt}{space 13}1967  {c |}{col 20}{res}{space 2} .0961993{col 32}{space 2} .0674808{col 43}{space 1}    1.43{col 52}{space 3}0.161{col 60}{space 4}-.0396325{col 73}{space 3} .2320312
{txt}{space 13}1968  {c |}{col 20}{res}{space 2} .1138598{col 32}{space 2} .0824783{col 43}{space 1}    1.38{col 52}{space 3}0.174{col 60}{space 4}-.0521603{col 73}{space 3} .2798799
{txt}{space 13}1969  {c |}{col 20}{res}{space 2} .2408889{col 32}{space 2} .1110851{col 43}{space 1}    2.17{col 52}{space 3}0.035{col 60}{space 4} .0172862{col 73}{space 3} .4644915
{txt}{space 13}1970  {c |}{col 20}{res}{space 2} .2224305{col 32}{space 2} .1097936{col 43}{space 1}    2.03{col 52}{space 3}0.049{col 60}{space 4} .0014274{col 73}{space 3} .4434336
{txt}{space 13}1971  {c |}{col 20}{res}{space 2} .1735905{col 32}{space 2} .1121154{col 43}{space 1}    1.55{col 52}{space 3}0.128{col 60}{space 4}-.0520861{col 73}{space 3} .3992671
{txt}{space 13}1972  {c |}{col 20}{res}{space 2} .2054423{col 32}{space 2} .1180065{col 43}{space 1}    1.74{col 52}{space 3}0.088{col 60}{space 4}-.0320924{col 73}{space 3}  .442977
{txt}{space 13}1973  {c |}{col 20}{res}{space 2} .2552283{col 32}{space 2} .1216213{col 43}{space 1}    2.10{col 52}{space 3}0.041{col 60}{space 4} .0104173{col 73}{space 3} .5000393
{txt}{space 13}1974  {c |}{col 20}{res}{space 2} .2581292{col 32}{space 2} .1248274{col 43}{space 1}    2.07{col 52}{space 3}0.044{col 60}{space 4} .0068646{col 73}{space 3} .5093938
{txt}{space 13}1975  {c |}{col 20}{res}{space 2}  .315036{col 32}{space 2} .1302002{col 43}{space 1}    2.42{col 52}{space 3}0.020{col 60}{space 4} .0529565{col 73}{space 3} .5771154
{txt}{space 13}1976  {c |}{col 20}{res}{space 2} .3414927{col 32}{space 2} .1355897{col 43}{space 1}    2.52{col 52}{space 3}0.015{col 60}{space 4} .0685649{col 73}{space 3} .6144206
{txt}{space 13}1977  {c |}{col 20}{res}{space 2} .3385471{col 32}{space 2} .1350786{col 43}{space 1}    2.51{col 52}{space 3}0.016{col 60}{space 4} .0666479{col 73}{space 3} .6104462
{txt}{space 13}1978  {c |}{col 20}{res}{space 2} .2946702{col 32}{space 2}  .139944{col 43}{space 1}    2.11{col 52}{space 3}0.041{col 60}{space 4} .0129775{col 73}{space 3} .5763629
{txt}{space 13}1979  {c |}{col 20}{res}{space 2} .2863101{col 32}{space 2} .1426461{col 43}{space 1}    2.01{col 52}{space 3}0.051{col 60}{space 4}-.0008217{col 73}{space 3} .5734418
{txt}{space 13}1980  {c |}{col 20}{res}{space 2} .2970239{col 32}{space 2}  .149009{col 43}{space 1}    1.99{col 52}{space 3}0.052{col 60}{space 4}-.0029157{col 73}{space 3} .5969635
{txt}{space 13}1981  {c |}{col 20}{res}{space 2} .3405818{col 32}{space 2} .1522079{col 43}{space 1}    2.24{col 52}{space 3}0.030{col 60}{space 4} .0342032{col 73}{space 3} .6469604
{txt}{space 13}1982  {c |}{col 20}{res}{space 2} .3103452{col 32}{space 2} .1521319{col 43}{space 1}    2.04{col 52}{space 3}0.047{col 60}{space 4} .0041194{col 73}{space 3} .6165709
{txt}{space 13}1983  {c |}{col 20}{res}{space 2} .3207682{col 32}{space 2} .1529428{col 43}{space 1}    2.10{col 52}{space 3}0.041{col 60}{space 4} .0129104{col 73}{space 3}  .628626
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 1.094086{col 32}{space 2} .1003579{col 43}{space 1}   10.90{col 52}{space 3}0.000{col 60}{space 4} .8920762{col 73}{space 3} 1.296096
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_asimple_divided_gov.tex"'"':Table_asimple_divided_gov.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_asimple_divided_gov.txt", label"':seeout}
{p 0 6 2}note: 50.state#c.year omitted because of collinearity{p_end}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       830
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}{help j_robustsingular##|_new:F(  23,     46)}{col 67}=          {res}.
{txt}{col 49}Prob > F{col 67}=          {res}.
{txt}{col 49}R-squared{col 67}= {res}    0.8376
{txt}{col 49}Adj R-squared{col 67}= {res}    0.8114
{txt}{col 49}Root MSE{col 67}= {res}    0.2846

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
simple_divided_gov {c |}{col 20}{res}{space 2} .0253706{col 32}{space 2} .0430506{col 43}{space 1}    0.59{col 52}{space 3}0.559{col 60}{space 4}-.0612859{col 73}{space 3}  .112027
{txt}{space 10}ideociti {c |}{col 20}{res}{space 2} .6296639{col 32}{space 2} .2536069{col 43}{space 1}    2.48{col 52}{space 3}0.017{col 60}{space 4} .1191797{col 73}{space 3} 1.140148
{txt}{space 13}urban {c |}{col 20}{res}{space 2} 4.325657{col 32}{space 2} 8.208999{col 43}{space 1}    0.53{col 52}{space 3}0.601{col 60}{space 4} -12.1982{col 73}{space 3} 20.84951
{txt}{space 12}income {c |}{col 20}{res}{space 2} .0374087{col 32}{space 2} .0860959{col 43}{space 1}    0.43{col 52}{space 3}0.666{col 60}{space 4}-.1358933{col 73}{space 3} .2107107
{txt}{space 10}lfullemp {c |}{col 20}{res}{space 2} .2353711{col 32}{space 2} .3848621{col 43}{space 1}    0.61{col 52}{space 3}0.544{col 60}{space 4}-.5393161{col 73}{space 3} 1.010058
{txt}{space 18} {c |}
{space 14}year {c |}
{space 13}1966  {c |}{col 20}{res}{space 2}-.0207547{col 32}{space 2} .0696317{col 43}{space 1}   -0.30{col 52}{space 3}0.767{col 60}{space 4}-.1609159{col 73}{space 3} .1194066
{txt}{space 13}1967  {c |}{col 20}{res}{space 2}-.0421546{col 32}{space 2} .1256552{col 43}{space 1}   -0.34{col 52}{space 3}0.739{col 60}{space 4}-.2950854{col 73}{space 3} .2107763
{txt}{space 13}1968  {c |}{col 20}{res}{space 2}-.1088475{col 32}{space 2} .1908193{col 43}{space 1}   -0.57{col 52}{space 3}0.571{col 60}{space 4}-.4929467{col 73}{space 3} .2752518
{txt}{space 13}1969  {c |}{col 20}{res}{space 2}-.0425762{col 32}{space 2} .2307243{col 43}{space 1}   -0.18{col 52}{space 3}0.854{col 60}{space 4}-.5070002{col 73}{space 3} .4218477
{txt}{space 13}1970  {c |}{col 20}{res}{space 2}-.1109939{col 32}{space 2} .2805828{col 43}{space 1}   -0.40{col 52}{space 3}0.694{col 60}{space 4}-.6757778{col 73}{space 3} .4537899
{txt}{space 13}1971  {c |}{col 20}{res}{space 2}-.2056572{col 32}{space 2} .3184243{col 43}{space 1}   -0.65{col 52}{space 3}0.522{col 60}{space 4}-.8466121{col 73}{space 3} .4352978
{txt}{space 13}1972  {c |}{col 20}{res}{space 2} -.206279{col 32}{space 2} .3703434{col 43}{space 1}   -0.56{col 52}{space 3}0.580{col 60}{space 4}-.9517415{col 73}{space 3} .5391835
{txt}{space 13}1973  {c |}{col 20}{res}{space 2}-.2515009{col 32}{space 2}  .422519{col 43}{space 1}   -0.60{col 52}{space 3}0.555{col 60}{space 4}-1.101987{col 73}{space 3} .5989857
{txt}{space 13}1974  {c |}{col 20}{res}{space 2}-.2656529{col 32}{space 2} .4298535{col 43}{space 1}   -0.62{col 52}{space 3}0.540{col 60}{space 4}-1.130903{col 73}{space 3} .5995974
{txt}{space 13}1975  {c |}{col 20}{res}{space 2}-.2570679{col 32}{space 2} .4673031{col 43}{space 1}   -0.55{col 52}{space 3}0.585{col 60}{space 4}  -1.1977{col 73}{space 3} .6835645
{txt}{space 13}1976  {c |}{col 20}{res}{space 2}-.2432227{col 32}{space 2} .5037147{col 43}{space 1}   -0.48{col 52}{space 3}0.631{col 60}{space 4}-1.257148{col 73}{space 3} .7707024
{txt}{space 13}1977  {c |}{col 20}{res}{space 2}-.2865254{col 32}{space 2} .5410408{col 43}{space 1}   -0.53{col 52}{space 3}0.599{col 60}{space 4}-1.375584{col 73}{space 3} .8025333
{txt}{space 13}1978  {c |}{col 20}{res}{space 2}-.3177283{col 32}{space 2} .5822504{col 43}{space 1}   -0.55{col 52}{space 3}0.588{col 60}{space 4}-1.489738{col 73}{space 3} .8542811
{txt}{space 13}1979  {c |}{col 20}{res}{space 2}-.3573934{col 32}{space 2} .6011831{col 43}{space 1}   -0.59{col 52}{space 3}0.555{col 60}{space 4}-1.567512{col 73}{space 3} .8527255
{txt}{space 13}1980  {c |}{col 20}{res}{space 2}-.3934105{col 32}{space 2} .5999402{col 43}{space 1}   -0.66{col 52}{space 3}0.515{col 60}{space 4}-1.601028{col 73}{space 3} .8142066
{txt}{space 13}1981  {c |}{col 20}{res}{space 2}-.4053658{col 32}{space 2}  .623487{col 43}{space 1}   -0.65{col 52}{space 3}0.519{col 60}{space 4} -1.66038{col 73}{space 3} .8496485
{txt}{space 13}1982  {c |}{col 20}{res}{space 2}-.4827039{col 32}{space 2} .6434612{col 43}{space 1}   -0.75{col 52}{space 3}0.457{col 60}{space 4}-1.777924{col 73}{space 3} .8125163
{txt}{space 13}1983  {c |}{col 20}{res}{space 2}-.5311594{col 32}{space 2} .6753893{col 43}{space 1}   -0.79{col 52}{space 3}0.436{col 60}{space 4}-1.890647{col 73}{space 3} .8283287
{txt}{space 18} {c |}
{space 6}state#c.year {c |}
{space 15}AL  {c |}{col 20}{res}{space 2}-.0069108{col 32}{space 2} .0134702{col 43}{space 1}   -0.51{col 52}{space 3}0.610{col 60}{space 4} -.034025{col 73}{space 3} .0202034
{txt}{space 15}AR  {c |}{col 20}{res}{space 2} .0971256{col 32}{space 2} .0095557{col 43}{space 1}   10.16{col 52}{space 3}0.000{col 60}{space 4} .0778909{col 73}{space 3} .1163602
{txt}{space 15}AZ  {c |}{col 20}{res}{space 2} .0854193{col 32}{space 2} .0199033{col 43}{space 1}    4.29{col 52}{space 3}0.000{col 60}{space 4} .0453561{col 73}{space 3} .1254824
{txt}{space 15}CA  {c |}{col 20}{res}{space 2}  .039473{col 32}{space 2} .0154863{col 43}{space 1}    2.55{col 52}{space 3}0.014{col 60}{space 4} .0083007{col 73}{space 3} .0706454
{txt}{space 15}CO  {c |}{col 20}{res}{space 2}-.0030563{col 32}{space 2} .0052474{col 43}{space 1}   -0.58{col 52}{space 3}0.563{col 60}{space 4}-.0136188{col 73}{space 3} .0075063
{txt}{space 15}CT  {c |}{col 20}{res}{space 2} .0669689{col 32}{space 2} .0205345{col 43}{space 1}    3.26{col 52}{space 3}0.002{col 60}{space 4}  .025635{col 73}{space 3} .1083028
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0304903{col 32}{space 2}  .025783{col 43}{space 1}    1.18{col 52}{space 3}0.243{col 60}{space 4}-.0214081{col 73}{space 3} .0823887
{txt}{space 15}FL  {c |}{col 20}{res}{space 2} .0791441{col 32}{space 2} .0099127{col 43}{space 1}    7.98{col 52}{space 3}0.000{col 60}{space 4} .0591908{col 73}{space 3} .0990974
{txt}{space 15}GA  {c |}{col 20}{res}{space 2}-.0868658{col 32}{space 2} .0133383{col 43}{space 1}   -6.51{col 52}{space 3}0.000{col 60}{space 4}-.1137144{col 73}{space 3}-.0600173
{txt}{space 15}IA  {c |}{col 20}{res}{space 2}  .048208{col 32}{space 2} .0133182{col 43}{space 1}    3.62{col 52}{space 3}0.001{col 60}{space 4} .0213998{col 73}{space 3} .0750162
{txt}{space 15}ID  {c |}{col 20}{res}{space 2} .1087143{col 32}{space 2} .0188492{col 43}{space 1}    5.77{col 52}{space 3}0.000{col 60}{space 4} .0707728{col 73}{space 3} .1466558
{txt}{space 15}IL  {c |}{col 20}{res}{space 2} .0116148{col 32}{space 2} .0218353{col 43}{space 1}    0.53{col 52}{space 3}0.597{col 60}{space 4}-.0323374{col 73}{space 3}  .055567
{txt}{space 15}IN  {c |}{col 20}{res}{space 2} -.058758{col 32}{space 2} .0270289{col 43}{space 1}   -2.17{col 52}{space 3}0.035{col 60}{space 4}-.1131643{col 73}{space 3}-.0043518
{txt}{space 15}KS  {c |}{col 20}{res}{space 2} .0081678{col 32}{space 2} .0125057{col 43}{space 1}    0.65{col 52}{space 3}0.517{col 60}{space 4}-.0170049{col 73}{space 3} .0333405
{txt}{space 15}KY  {c |}{col 20}{res}{space 2} .0072128{col 32}{space 2} .0210136{col 43}{space 1}    0.34{col 52}{space 3}0.733{col 60}{space 4}-.0350854{col 73}{space 3} .0495111
{txt}{space 15}LA  {c |}{col 20}{res}{space 2}-.0039823{col 32}{space 2}  .007909{col 43}{space 1}   -0.50{col 52}{space 3}0.617{col 60}{space 4}-.0199024{col 73}{space 3} .0119377
{txt}{space 15}MA  {c |}{col 20}{res}{space 2} .0141647{col 32}{space 2} .0281428{col 43}{space 1}    0.50{col 52}{space 3}0.617{col 60}{space 4}-.0424838{col 73}{space 3} .0708132
{txt}{space 15}MD  {c |}{col 20}{res}{space 2}  -.00742{col 32}{space 2} .0121308{col 43}{space 1}   -0.61{col 52}{space 3}0.544{col 60}{space 4} -.031838{col 73}{space 3} .0169981
{txt}{space 15}ME  {c |}{col 20}{res}{space 2}-.0407001{col 32}{space 2} .0475583{col 43}{space 1}   -0.86{col 52}{space 3}0.397{col 60}{space 4}  -.13643{col 73}{space 3} .0550299
{txt}{space 15}MI  {c |}{col 20}{res}{space 2} .0250693{col 32}{space 2} .0436954{col 43}{space 1}    0.57{col 52}{space 3}0.569{col 60}{space 4} -.062885{col 73}{space 3} .1130237
{txt}{space 15}MN  {c |}{col 20}{res}{space 2}-.0694531{col 32}{space 2} .0141756{col 43}{space 1}   -4.90{col 52}{space 3}0.000{col 60}{space 4}-.0979872{col 73}{space 3}-.0409191
{txt}{space 15}MO  {c |}{col 20}{res}{space 2} .0895387{col 32}{space 2} .0305177{col 43}{space 1}    2.93{col 52}{space 3}0.005{col 60}{space 4} .0281098{col 73}{space 3} .1509676
{txt}{space 15}MS  {c |}{col 20}{res}{space 2} .0664444{col 32}{space 2} .0118098{col 43}{space 1}    5.63{col 52}{space 3}0.000{col 60}{space 4} .0426725{col 73}{space 3} .0902162
{txt}{space 15}MT  {c |}{col 20}{res}{space 2} .1644142{col 32}{space 2} .0227361{col 43}{space 1}    7.23{col 52}{space 3}0.000{col 60}{space 4} .1186487{col 73}{space 3} .2101796
{txt}{space 15}NC  {c |}{col 20}{res}{space 2}-.0133724{col 32}{space 2} .0118824{col 43}{space 1}   -1.13{col 52}{space 3}0.266{col 60}{space 4}-.0372905{col 73}{space 3} .0105456
{txt}{space 15}ND  {c |}{col 20}{res}{space 2} .1247237{col 32}{space 2} .0239523{col 43}{space 1}    5.21{col 52}{space 3}0.000{col 60}{space 4} .0765103{col 73}{space 3} .1729372
{txt}{space 15}NH  {c |}{col 20}{res}{space 2} .0350389{col 32}{space 2}   .05226{col 43}{space 1}    0.67{col 52}{space 3}0.506{col 60}{space 4}-.0701549{col 73}{space 3} .1402328
{txt}{space 15}NJ  {c |}{col 20}{res}{space 2} .0421521{col 32}{space 2} .0230441{col 43}{space 1}    1.83{col 52}{space 3}0.074{col 60}{space 4}-.0042333{col 73}{space 3} .0885374
{txt}{space 15}NM  {c |}{col 20}{res}{space 2}-.0743988{col 32}{space 2} .0142302{col 43}{space 1}   -5.23{col 52}{space 3}0.000{col 60}{space 4}-.1030427{col 73}{space 3}-.0457549
{txt}{space 15}NV  {c |}{col 20}{res}{space 2} -.018007{col 32}{space 2} .0272307{col 43}{space 1}   -0.66{col 52}{space 3}0.512{col 60}{space 4}-.0728194{col 73}{space 3} .0368055
{txt}{space 15}NY  {c |}{col 20}{res}{space 2} .0226536{col 32}{space 2} .0343258{col 43}{space 1}    0.66{col 52}{space 3}0.513{col 60}{space 4}-.0464407{col 73}{space 3} .0917479
{txt}{space 15}OH  {c |}{col 20}{res}{space 2} .0876704{col 32}{space 2} .0329299{col 43}{space 1}    2.66{col 52}{space 3}0.011{col 60}{space 4}  .021386{col 73}{space 3} .1539548
{txt}{space 15}OK  {c |}{col 20}{res}{space 2} .0088634{col 32}{space 2} .0195377{col 43}{space 1}    0.45{col 52}{space 3}0.652{col 60}{space 4} -.030464{col 73}{space 3} .0481908
{txt}{space 15}OR  {c |}{col 20}{res}{space 2}-.0720927{col 32}{space 2} .0116241{col 43}{space 1}   -6.20{col 52}{space 3}0.000{col 60}{space 4}-.0954907{col 73}{space 3}-.0486947
{txt}{space 15}PA  {c |}{col 20}{res}{space 2} .0865738{col 32}{space 2} .0394285{col 43}{space 1}    2.20{col 52}{space 3}0.033{col 60}{space 4} .0072084{col 73}{space 3} .1659392
{txt}{space 15}RI  {c |}{col 20}{res}{space 2}-.0080208{col 32}{space 2} .0277991{col 43}{space 1}   -0.29{col 52}{space 3}0.774{col 60}{space 4}-.0639774{col 73}{space 3} .0479359
{txt}{space 15}SC  {c |}{col 20}{res}{space 2} .0745079{col 32}{space 2} .0281442{col 43}{space 1}    2.65{col 52}{space 3}0.011{col 60}{space 4} .0178566{col 73}{space 3} .1311592
{txt}{space 15}SD  {c |}{col 20}{res}{space 2} .0801772{col 32}{space 2} .0125976{col 43}{space 1}    6.36{col 52}{space 3}0.000{col 60}{space 4} .0548195{col 73}{space 3} .1055348
{txt}{space 15}TN  {c |}{col 20}{res}{space 2}-.0046721{col 32}{space 2}  .011234{col 43}{space 1}   -0.42{col 52}{space 3}0.679{col 60}{space 4}-.0272851{col 73}{space 3} .0179408
{txt}{space 15}TX  {c |}{col 20}{res}{space 2} .0004202{col 32}{space 2} .0155924{col 43}{space 1}    0.03{col 52}{space 3}0.979{col 60}{space 4}-.0309656{col 73}{space 3} .0318061
{txt}{space 15}UT  {c |}{col 20}{res}{space 2}-.0149758{col 32}{space 2} .0203785{col 43}{space 1}   -0.73{col 52}{space 3}0.466{col 60}{space 4}-.0559955{col 73}{space 3} .0260439
{txt}{space 15}VA  {c |}{col 20}{res}{space 2}-.0153136{col 32}{space 2} .0115312{col 43}{space 1}   -1.33{col 52}{space 3}0.191{col 60}{space 4}-.0385247{col 73}{space 3} .0078974
{txt}{space 15}VT  {c |}{col 20}{res}{space 2} .0064686{col 32}{space 2} .0278228{col 43}{space 1}    0.23{col 52}{space 3}0.817{col 60}{space 4}-.0495358{col 73}{space 3}  .062473
{txt}{space 15}WA  {c |}{col 20}{res}{space 2} .0062193{col 32}{space 2} .0151531{col 43}{space 1}    0.41{col 52}{space 3}0.683{col 60}{space 4}-.0242823{col 73}{space 3} .0367209
{txt}{space 15}WI  {c |}{col 20}{res}{space 2}-.0190732{col 32}{space 2} .0294992{col 43}{space 1}   -0.65{col 52}{space 3}0.521{col 60}{space 4} -.078452{col 73}{space 3} .0403057
{txt}{space 15}WV  {c |}{col 20}{res}{space 2}  .024378{col 32}{space 2} .0401214{col 43}{space 1}    0.61{col 52}{space 3}0.546{col 60}{space 4}-.0563821{col 73}{space 3} .1051381
{txt}{space 15}WY  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}-45.31425{col 32}{space 2} 33.80675{col 43}{space 1}   -1.34{col 52}{space 3}0.187{col 60}{space 4}-113.3637{col 73}{space 3} 22.73522
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_asimple_divided_gov.tex"'"':Table_asimple_divided_gov.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_asimple_divided_gov.txt", label"':seeout}

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -803.7917}  
Iteration 1:{space 3}log pseudolikelihood = {res:-417.04289}  
Iteration 2:{space 3}log pseudolikelihood = {res:-384.17464}  
Iteration 3:{space 3}log pseudolikelihood = {res:-377.41541}  
Iteration 4:{space 3}log pseudolikelihood = {res: -376.5525}  
Iteration 5:{space 3}log pseudolikelihood = {res:-376.34253}  
Iteration 6:{space 3}log pseudolikelihood = {res:-376.29783}  
Iteration 7:{space 3}log pseudolikelihood = {res:-376.28759}  
Iteration 8:{space 3}log pseudolikelihood = {res:-376.28589}  
Iteration 9:{space 3}log pseudolikelihood = {res: -376.2857}  
Iteration 10:{space 2}log pseudolikelihood = {res:-376.28566}  
Iteration 11:{space 2}log pseudolikelihood = {res:-376.28565}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       830
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(31)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-376.28565{txt}{col 49}Pseudo R2{col 67}= {res}    0.5319

{txt}{ralign 90:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}civil_service_reform_ipe{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}simple_divided_gov {c |}{col 26}{res}{space 2} .2429016{col 38}{space 2} .3726731{col 49}{space 1}    0.65{col 58}{space 3}0.515{col 66}{space 4}-.4875242{col 79}{space 3} .9733274
{txt}{space 16}ideociti {c |}{col 26}{res}{space 2} 8.074538{col 38}{space 2} 2.899459{col 49}{space 1}    2.78{col 58}{space 3}0.005{col 66}{space 4} 2.391703{col 79}{space 3} 13.75737
{txt}{space 19}urban {c |}{col 26}{res}{space 2}  46.6372{col 38}{space 2} 29.84297{col 49}{space 1}    1.56{col 58}{space 3}0.118{col 66}{space 4}-11.85394{col 79}{space 3} 105.1283
{txt}{space 18}income {c |}{col 26}{res}{space 2}-.1547365{col 38}{space 2} .4253689{col 49}{space 1}   -0.36{col 58}{space 3}0.716{col 66}{space 4}-.9884443{col 79}{space 3} .6789712
{txt}{space 16}lfullemp {c |}{col 26}{res}{space 2}-2.781159{col 38}{space 2} 4.219632{col 49}{space 1}   -0.66{col 58}{space 3}0.510{col 66}{space 4}-11.05149{col 79}{space 3} 5.489168
{txt}{space 24} {c |}
{space 20}year {c |}
{space 19}1966  {c |}{col 26}{res}{space 2} .3972297{col 38}{space 2} .4104355{col 49}{space 1}    0.97{col 58}{space 3}0.333{col 66}{space 4}-.4072092{col 79}{space 3} 1.201669
{txt}{space 19}1967  {c |}{col 26}{res}{space 2} .6584658{col 38}{space 2} .6633953{col 49}{space 1}    0.99{col 58}{space 3}0.321{col 66}{space 4}-.6417651{col 79}{space 3} 1.958697
{txt}{space 19}1968  {c |}{col 26}{res}{space 2} .7000782{col 38}{space 2} .9811834{col 49}{space 1}    0.71{col 58}{space 3}0.476{col 66}{space 4}-1.223006{col 79}{space 3} 2.623162
{txt}{space 19}1969  {c |}{col 26}{res}{space 2} 1.180927{col 38}{space 2} 1.084934{col 49}{space 1}    1.09{col 58}{space 3}0.276{col 66}{space 4}-.9455042{col 79}{space 3} 3.307359
{txt}{space 19}1970  {c |}{col 26}{res}{space 2} 1.228439{col 38}{space 2} 1.259499{col 49}{space 1}    0.98{col 58}{space 3}0.329{col 66}{space 4}-1.240135{col 79}{space 3} 3.697012
{txt}{space 19}1971  {c |}{col 26}{res}{space 2} .7853326{col 38}{space 2} 1.403169{col 49}{space 1}    0.56{col 58}{space 3}0.576{col 66}{space 4}-1.964828{col 79}{space 3} 3.535493
{txt}{space 19}1972  {c |}{col 26}{res}{space 2} 1.491945{col 38}{space 2} 1.765935{col 49}{space 1}    0.84{col 58}{space 3}0.398{col 66}{space 4}-1.969224{col 79}{space 3} 4.953114
{txt}{space 19}1973  {c |}{col 26}{res}{space 2} 1.507302{col 38}{space 2} 2.047065{col 49}{space 1}    0.74{col 58}{space 3}0.462{col 66}{space 4}-2.504871{col 79}{space 3} 5.519476
{txt}{space 19}1974  {c |}{col 26}{res}{space 2} 1.664058{col 38}{space 2} 2.142174{col 49}{space 1}    0.78{col 58}{space 3}0.437{col 66}{space 4}-2.534526{col 79}{space 3} 5.862642
{txt}{space 19}1975  {c |}{col 26}{res}{space 2}  1.69304{col 38}{space 2} 2.291705{col 49}{space 1}    0.74{col 58}{space 3}0.460{col 66}{space 4}-2.798619{col 79}{space 3} 6.184699
{txt}{space 19}1976  {c |}{col 26}{res}{space 2} 2.343316{col 38}{space 2} 2.350217{col 49}{space 1}    1.00{col 58}{space 3}0.319{col 66}{space 4}-2.263026{col 79}{space 3} 6.949657
{txt}{space 19}1977  {c |}{col 26}{res}{space 2} 2.496991{col 38}{space 2} 2.520939{col 49}{space 1}    0.99{col 58}{space 3}0.322{col 66}{space 4}-2.443958{col 79}{space 3}  7.43794
{txt}{space 19}1978  {c |}{col 26}{res}{space 2} 2.644181{col 38}{space 2} 2.691731{col 49}{space 1}    0.98{col 58}{space 3}0.326{col 66}{space 4}-2.631516{col 79}{space 3} 7.919877
{txt}{space 19}1979  {c |}{col 26}{res}{space 2} 2.549784{col 38}{space 2} 2.835111{col 49}{space 1}    0.90{col 58}{space 3}0.368{col 66}{space 4}-3.006931{col 79}{space 3}   8.1065
{txt}{space 19}1980  {c |}{col 26}{res}{space 2} 2.537813{col 38}{space 2} 2.786485{col 49}{space 1}    0.91{col 58}{space 3}0.362{col 66}{space 4}-2.923597{col 79}{space 3} 7.999223
{txt}{space 19}1981  {c |}{col 26}{res}{space 2} 2.733542{col 38}{space 2} 2.758258{col 49}{space 1}    0.99{col 58}{space 3}0.322{col 66}{space 4}-2.672544{col 79}{space 3} 8.139629
{txt}{space 19}1982  {c |}{col 26}{res}{space 2}  2.03675{col 38}{space 2} 2.714917{col 49}{space 1}    0.75{col 58}{space 3}0.453{col 66}{space 4}-3.284391{col 79}{space 3}  7.35789
{txt}{space 19}1983  {c |}{col 26}{res}{space 2} 1.953139{col 38}{space 2} 2.704521{col 49}{space 1}    0.72{col 58}{space 3}0.470{col 66}{space 4}-3.347624{col 79}{space 3} 7.253902
{txt}{space 24} {c |}
{space 19}state {c |}
{space 21}AR  {c |}{col 26}{res}{space 2}-16.13305{col 38}{space 2} 2.989949{col 49}{space 1}   -5.40{col 58}{space 3}0.000{col 66}{space 4}-21.99325{col 79}{space 3}-10.27286
{txt}{space 21}AZ  {c |}{col 26}{res}{space 2}-30.29574{col 38}{space 2} 7.564299{col 49}{space 1}   -4.01{col 58}{space 3}0.000{col 66}{space 4} -45.1215{col 79}{space 3}-15.46999
{txt}{space 21}CA  {c |}{col 26}{res}{space 2}-31.54052{col 38}{space 2} 9.482721{col 49}{space 1}   -3.33{col 58}{space 3}0.001{col 66}{space 4}-50.12631{col 79}{space 3}-12.95472
{txt}{space 21}CO  {c |}{col 26}{res}{space 2}-32.58902{col 38}{space 2} 6.272268{col 49}{space 1}   -5.20{col 58}{space 3}0.000{col 66}{space 4}-44.88244{col 79}{space 3} -20.2956
{txt}{space 21}CT  {c |}{col 26}{res}{space 2}-32.17116{col 38}{space 2} 5.971031{col 49}{space 1}   -5.39{col 58}{space 3}0.000{col 66}{space 4}-43.87416{col 79}{space 3}-20.46816
{txt}{space 21}DE  {c |}{col 26}{res}{space 2} -32.2212{col 38}{space 2} 7.083437{col 49}{space 1}   -4.55{col 58}{space 3}0.000{col 66}{space 4}-46.10448{col 79}{space 3}-18.33791
{txt}{space 21}FL  {c |}{col 26}{res}{space 2}-26.95908{col 38}{space 2} 6.515499{col 49}{space 1}   -4.14{col 58}{space 3}0.000{col 66}{space 4}-39.72923{col 79}{space 3}-14.18894
{txt}{space 21}GA  {c |}{col 26}{res}{space 2} -18.5229{col 38}{space 2} 1.928859{col 49}{space 1}   -9.60{col 58}{space 3}0.000{col 66}{space 4} -22.3034{col 79}{space 3}-14.74241
{txt}{space 21}IA  {c |}{col 26}{res}{space 2}-18.37208{col 38}{space 2}  2.20536{col 49}{space 1}   -8.33{col 58}{space 3}0.000{col 66}{space 4} -22.6945{col 79}{space 3}-14.04965
{txt}{space 21}ID  {c |}{col 26}{res}{space 2}-20.13334{col 38}{space 2} 5.332208{col 49}{space 1}   -3.78{col 58}{space 3}0.000{col 66}{space 4}-30.58427{col 79}{space 3}-9.682403
{txt}{space 21}IL  {c |}{col 26}{res}{space 2} -31.7979{col 38}{space 2} 6.890837{col 49}{space 1}   -4.61{col 58}{space 3}0.000{col 66}{space 4}-45.30369{col 79}{space 3}-18.29211
{txt}{space 21}IN  {c |}{col 26}{res}{space 2}-22.79581{col 38}{space 2} 2.202869{col 49}{space 1}  -10.35{col 58}{space 3}0.000{col 66}{space 4}-27.11335{col 79}{space 3}-18.47826
{txt}{space 21}KS  {c |}{col 26}{res}{space 2}-5.773323{col 38}{space 2} 3.087103{col 49}{space 1}   -1.87{col 58}{space 3}0.061{col 66}{space 4}-11.82393{col 79}{space 3} .2772882
{txt}{space 21}KY  {c |}{col 26}{res}{space 2}-18.89277{col 38}{space 2} 2.973383{col 49}{space 1}   -6.35{col 58}{space 3}0.000{col 66}{space 4}-24.72049{col 79}{space 3}-13.06505
{txt}{space 21}LA  {c |}{col 26}{res}{space 2}-3.073247{col 38}{space 2} 2.917081{col 49}{space 1}   -1.05{col 58}{space 3}0.292{col 66}{space 4}-8.790621{col 79}{space 3} 2.644127
{txt}{space 21}MA  {c |}{col 26}{res}{space 2}-15.07559{col 38}{space 2} 7.183984{col 49}{space 1}   -2.10{col 58}{space 3}0.036{col 66}{space 4}-29.15594{col 79}{space 3}-.9952382
{txt}{space 21}MD  {c |}{col 26}{res}{space 2}-31.79398{col 38}{space 2} 5.462569{col 49}{space 1}   -5.82{col 58}{space 3}0.000{col 66}{space 4}-42.50041{col 79}{space 3}-21.08754
{txt}{space 21}ME  {c |}{col 26}{res}{space 2} -19.7854{col 38}{space 2} 4.739584{col 49}{space 1}   -4.17{col 58}{space 3}0.000{col 66}{space 4}-29.07481{col 79}{space 3}-10.49599
{txt}{space 21}MI  {c |}{col 26}{res}{space 2}-7.136508{col 38}{space 2} 4.611818{col 49}{space 1}   -1.55{col 58}{space 3}0.122{col 66}{space 4}-16.17551{col 79}{space 3} 1.902489
{txt}{space 21}MN  {c |}{col 26}{res}{space 2}-25.20095{col 38}{space 2} 2.802528{col 49}{space 1}   -8.99{col 58}{space 3}0.000{col 66}{space 4}-30.69381{col 79}{space 3} -19.7081
{txt}{space 21}MO  {c |}{col 26}{res}{space 2}-24.73275{col 38}{space 2} 3.108392{col 49}{space 1}   -7.96{col 58}{space 3}0.000{col 66}{space 4}-30.82509{col 79}{space 3}-18.64042
{txt}{space 21}MS  {c |}{col 26}{res}{space 2} -18.1418{col 38}{space 2} 3.879933{col 49}{space 1}   -4.68{col 58}{space 3}0.000{col 66}{space 4}-25.74633{col 79}{space 3}-10.53727
{txt}{space 21}MT  {c |}{col 26}{res}{space 2}-24.86988{col 38}{space 2} 5.112631{col 49}{space 1}   -4.86{col 58}{space 3}0.000{col 66}{space 4}-34.89045{col 79}{space 3}-14.84931
{txt}{space 21}NC  {c |}{col 26}{res}{space 2} 7.771037{col 38}{space 2} 5.366831{col 49}{space 1}    1.45{col 58}{space 3}0.148{col 66}{space 4}-2.747759{col 79}{space 3} 18.28983
{txt}{space 21}ND  {c |}{col 26}{res}{space 2}-22.56371{col 38}{space 2} 6.395114{col 49}{space 1}   -3.53{col 58}{space 3}0.000{col 66}{space 4} -35.0979{col 79}{space 3}-10.02952
{txt}{space 21}NH  {c |}{col 26}{res}{space 2}-18.79849{col 38}{space 2} 5.851863{col 49}{space 1}   -3.21{col 58}{space 3}0.001{col 66}{space 4}-30.26793{col 79}{space 3}-7.329053
{txt}{space 21}NJ  {c |}{col 26}{res}{space 2} -36.5274{col 38}{space 2} 8.410263{col 49}{space 1}   -4.34{col 58}{space 3}0.000{col 66}{space 4}-53.01121{col 79}{space 3}-20.04358
{txt}{space 21}NM  {c |}{col 26}{res}{space 2}-26.54947{col 38}{space 2} 5.139028{col 49}{space 1}   -5.17{col 58}{space 3}0.000{col 66}{space 4}-36.62178{col 79}{space 3}-16.47716
{txt}{space 21}NV  {c |}{col 26}{res}{space 2}-14.86759{col 38}{space 2} 10.75076{col 49}{space 1}   -1.38{col 58}{space 3}0.167{col 66}{space 4}-35.93868{col 79}{space 3}  6.20351
{txt}{space 21}NY  {c |}{col 26}{res}{space 2}-32.02991{col 38}{space 2} 8.365717{col 49}{space 1}   -3.83{col 58}{space 3}0.000{col 66}{space 4}-48.42641{col 79}{space 3}-15.63341
{txt}{space 21}OH  {c |}{col 26}{res}{space 2}-26.43662{col 38}{space 2} 4.899478{col 49}{space 1}   -5.40{col 58}{space 3}0.000{col 66}{space 4}-36.03942{col 79}{space 3}-16.83382
{txt}{space 21}OK  {c |}{col 26}{res}{space 2}-4.964877{col 38}{space 2} 2.813937{col 49}{space 1}   -1.76{col 58}{space 3}0.078{col 66}{space 4}-10.48009{col 79}{space 3} .5503378
{txt}{space 21}OR  {c |}{col 26}{res}{space 2}-27.09992{col 38}{space 2} 3.364112{col 49}{space 1}   -8.06{col 58}{space 3}0.000{col 66}{space 4}-33.69346{col 79}{space 3}-20.50639
{txt}{space 21}PA  {c |}{col 26}{res}{space 2}-24.22401{col 38}{space 2} 5.185487{col 49}{space 1}   -4.67{col 58}{space 3}0.000{col 66}{space 4}-34.38738{col 79}{space 3}-14.06064
{txt}{space 21}RI  {c |}{col 26}{res}{space 2}-37.67502{col 38}{space 2} 10.30133{col 49}{space 1}   -3.66{col 58}{space 3}0.000{col 66}{space 4}-57.86525{col 79}{space 3}-17.48479
{txt}{space 21}SC  {c |}{col 26}{res}{space 2}-14.00169{col 38}{space 2} 2.983175{col 49}{space 1}   -4.69{col 58}{space 3}0.000{col 66}{space 4} -19.8486{col 79}{space 3}-8.154772
{txt}{space 21}SD  {c |}{col 26}{res}{space 2}-22.57342{col 38}{space 2}  6.33048{col 49}{space 1}   -3.57{col 58}{space 3}0.000{col 66}{space 4}-34.98093{col 79}{space 3} -10.1659
{txt}{space 21}TN  {c |}{col 26}{res}{space 2}-21.88926{col 38}{space 2} 1.797474{col 49}{space 1}  -12.18{col 58}{space 3}0.000{col 66}{space 4}-25.41225{col 79}{space 3}-18.36628
{txt}{space 21}TX  {c |}{col 26}{res}{space 2} -55.6277{col 38}{space 2} 6.492605{col 49}{space 1}   -8.57{col 58}{space 3}0.000{col 66}{space 4}-68.35297{col 79}{space 3}-42.90242
{txt}{space 21}UT  {c |}{col 26}{res}{space 2}-29.60616{col 38}{space 2} 8.206567{col 49}{space 1}   -3.61{col 58}{space 3}0.000{col 66}{space 4}-45.69074{col 79}{space 3}-13.52159
{txt}{space 21}VA  {c |}{col 26}{res}{space 2}-21.25438{col 38}{space 2} 2.773702{col 49}{space 1}   -7.66{col 58}{space 3}0.000{col 66}{space 4}-26.69074{col 79}{space 3}-15.81802
{txt}{space 21}VT  {c |}{col 26}{res}{space 2}-15.03152{col 38}{space 2} 8.655949{col 49}{space 1}   -1.74{col 58}{space 3}0.082{col 66}{space 4}-31.99687{col 79}{space 3} 1.933828
{txt}{space 21}WA  {c |}{col 26}{res}{space 2} -29.7974{col 38}{space 2} 4.325657{col 49}{space 1}   -6.89{col 58}{space 3}0.000{col 66}{space 4}-38.27553{col 79}{space 3}-21.31927
{txt}{space 21}WI  {c |}{col 26}{res}{space 2}-21.66936{col 38}{space 2} 2.554197{col 49}{space 1}   -8.48{col 58}{space 3}0.000{col 66}{space 4} -26.6755{col 79}{space 3}-16.66323
{txt}{space 21}WV  {c |}{col 26}{res}{space 2}-42.45314{col 38}{space 2} 6.443346{col 49}{space 1}   -6.59{col 58}{space 3}0.000{col 66}{space 4}-55.08187{col 79}{space 3}-29.82442
{txt}{space 21}WY  {c |}{col 26}{res}{space 2}-27.45468{col 38}{space 2} 7.797014{col 49}{space 1}   -3.52{col 58}{space 3}0.000{col 66}{space 4}-42.73654{col 79}{space 3}-12.17281
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}/cut1 {c |}{col 26}{res}{space 2}-23.55946{col 38}{space 2} 41.08209{col 66}{space 4}-104.0789{col 79}{space 3} 56.95996
{txt}{space 19}/cut2 {c |}{col 26}{res}{space 2}-18.86925{col 38}{space 2} 41.10718{col 66}{space 4}-99.43784{col 79}{space 3} 61.69934
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 188 observations completely determined.{txt}  Standard errors questionable.{p_end}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_asimple_divided_gov.tex"'"':Table_asimple_divided_gov.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_asimple_divided_gov.txt", label"':seeout}
{p 0 6 2}note: 50.state#c.year omitted because of collinearity{p_end}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       893
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}{help j_robustsingular##|_new:F(  22,     46)}{col 67}=          {res}.
{txt}{col 49}Prob > F{col 67}=          {res}.
{txt}{col 49}R-squared{col 67}= {res}    0.8471
{txt}{col 49}Adj R-squared{col 67}= {res}    0.8245
{txt}{col 49}Root MSE{col 67}= {res}    0.1255

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~m{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
simple_divided_gov {c |}{col 20}{res}{space 2}-.0012659{col 32}{space 2} .0149752{col 43}{space 1}   -0.08{col 52}{space 3}0.933{col 60}{space 4}-.0314094{col 73}{space 3} .0288776
{txt}{space 10}ideociti {c |}{col 20}{res}{space 2} .0228711{col 32}{space 2}  .138708{col 43}{space 1}    0.16{col 52}{space 3}0.870{col 60}{space 4}-.2563336{col 73}{space 3} .3020758
{txt}{space 13}urban {c |}{col 20}{res}{space 2} 3.382411{col 32}{space 2}  3.69416{col 43}{space 1}    0.92{col 52}{space 3}0.365{col 60}{space 4}-4.053548{col 73}{space 3} 10.81837
{txt}{space 12}income {c |}{col 20}{res}{space 2} .0240135{col 32}{space 2} .0433699{col 43}{space 1}    0.55{col 52}{space 3}0.582{col 60}{space 4}-.0632856{col 73}{space 3} .1113125
{txt}{space 10}lfullemp {c |}{col 20}{res}{space 2} -.007399{col 32}{space 2} .1383599{col 43}{space 1}   -0.05{col 52}{space 3}0.958{col 60}{space 4}-.2859031{col 73}{space 3} .2711051
{txt}{space 18} {c |}
{space 14}year {c |}
{space 13}1966  {c |}{col 20}{res}{space 2} .0034036{col 32}{space 2} .0380304{col 43}{space 1}    0.09{col 52}{space 3}0.929{col 60}{space 4}-.0731477{col 73}{space 3} .0799549
{txt}{space 13}1967  {c |}{col 20}{res}{space 2} .0077812{col 32}{space 2} .0497437{col 43}{space 1}    0.16{col 52}{space 3}0.876{col 60}{space 4}-.0923477{col 73}{space 3} .1079101
{txt}{space 13}1968  {c |}{col 20}{res}{space 2}-.0109366{col 32}{space 2} .0781973{col 43}{space 1}   -0.14{col 52}{space 3}0.889{col 60}{space 4}-.1683396{col 73}{space 3} .1464664
{txt}{space 13}1969  {c |}{col 20}{res}{space 2}-.0085092{col 32}{space 2} .0950373{col 43}{space 1}   -0.09{col 52}{space 3}0.929{col 60}{space 4}-.1998094{col 73}{space 3}  .182791
{txt}{space 13}1970  {c |}{col 20}{res}{space 2}-.0420028{col 32}{space 2} .1120211{col 43}{space 1}   -0.37{col 52}{space 3}0.709{col 60}{space 4}-.2674897{col 73}{space 3} .1834841
{txt}{space 13}1971  {c |}{col 20}{res}{space 2}-.0685493{col 32}{space 2} .1261909{col 43}{space 1}   -0.54{col 52}{space 3}0.590{col 60}{space 4}-.3225585{col 73}{space 3} .1854598
{txt}{space 13}1972  {c |}{col 20}{res}{space 2}-.1024639{col 32}{space 2} .1492324{col 43}{space 1}   -0.69{col 52}{space 3}0.496{col 60}{space 4}-.4028531{col 73}{space 3} .1979254
{txt}{space 13}1973  {c |}{col 20}{res}{space 2}-.1181755{col 32}{space 2} .1673306{col 43}{space 1}   -0.71{col 52}{space 3}0.484{col 60}{space 4}-.4549944{col 73}{space 3} .2186435
{txt}{space 13}1974  {c |}{col 20}{res}{space 2}-.1329584{col 32}{space 2} .1673055{col 43}{space 1}   -0.79{col 52}{space 3}0.431{col 60}{space 4}-.4697269{col 73}{space 3} .2038101
{txt}{space 13}1975  {c |}{col 20}{res}{space 2}-.1303521{col 32}{space 2} .1869849{col 43}{space 1}   -0.70{col 52}{space 3}0.489{col 60}{space 4}-.5067332{col 73}{space 3}  .246029
{txt}{space 13}1976  {c |}{col 20}{res}{space 2}-.1161528{col 32}{space 2} .2080602{col 43}{space 1}   -0.56{col 52}{space 3}0.579{col 60}{space 4}-.5349562{col 73}{space 3} .3026507
{txt}{space 13}1977  {c |}{col 20}{res}{space 2}-.1443485{col 32}{space 2} .2256637{col 43}{space 1}   -0.64{col 52}{space 3}0.526{col 60}{space 4}-.5985861{col 73}{space 3} .3098891
{txt}{space 13}1978  {c |}{col 20}{res}{space 2}-.1756439{col 32}{space 2} .2463894{col 43}{space 1}   -0.71{col 52}{space 3}0.480{col 60}{space 4}-.6716001{col 73}{space 3} .3203124
{txt}{space 13}1979  {c |}{col 20}{res}{space 2} -.195379{col 32}{space 2} .2537763{col 43}{space 1}   -0.77{col 52}{space 3}0.445{col 60}{space 4}-.7062042{col 73}{space 3} .3154462
{txt}{space 13}1980  {c |}{col 20}{res}{space 2}-.2073813{col 32}{space 2} .2499802{col 43}{space 1}   -0.83{col 52}{space 3}0.411{col 60}{space 4}-.7105654{col 73}{space 3} .2958027
{txt}{space 13}1981  {c |}{col 20}{res}{space 2}-.2325563{col 32}{space 2} .2622345{col 43}{space 1}   -0.89{col 52}{space 3}0.380{col 60}{space 4}-.7604069{col 73}{space 3} .2952943
{txt}{space 13}1982  {c |}{col 20}{res}{space 2}-.2560249{col 32}{space 2} .2738204{col 43}{space 1}   -0.94{col 52}{space 3}0.355{col 60}{space 4}-.8071968{col 73}{space 3} .2951469
{txt}{space 13}1983  {c |}{col 20}{res}{space 2}-.2844063{col 32}{space 2} .2914165{col 43}{space 1}   -0.98{col 52}{space 3}0.334{col 60}{space 4}-.8709974{col 73}{space 3} .3021847
{txt}{space 18} {c |}
{space 6}state#c.year {c |}
{space 15}AL  {c |}{col 20}{res}{space 2} .0052123{col 32}{space 2} .0059321{col 43}{space 1}    0.88{col 52}{space 3}0.384{col 60}{space 4}-.0067284{col 73}{space 3}  .017153
{txt}{space 15}AR  {c |}{col 20}{res}{space 2} .0544471{col 32}{space 2} .0049193{col 43}{space 1}   11.07{col 52}{space 3}0.000{col 60}{space 4}  .044545{col 73}{space 3} .0643491
{txt}{space 15}AZ  {c |}{col 20}{res}{space 2} .0384945{col 32}{space 2} .0096867{col 43}{space 1}    3.97{col 52}{space 3}0.000{col 60}{space 4} .0189961{col 73}{space 3} .0579928
{txt}{space 15}CA  {c |}{col 20}{res}{space 2} .0068319{col 32}{space 2} .0066335{col 43}{space 1}    1.03{col 52}{space 3}0.308{col 60}{space 4}-.0065207{col 73}{space 3} .0201845
{txt}{space 15}CO  {c |}{col 20}{res}{space 2} .0008995{col 32}{space 2} .0024482{col 43}{space 1}    0.37{col 52}{space 3}0.715{col 60}{space 4}-.0040285{col 73}{space 3} .0058275
{txt}{space 15}CT  {c |}{col 20}{res}{space 2} .0092595{col 32}{space 2} .0085262{col 43}{space 1}    1.09{col 52}{space 3}0.283{col 60}{space 4}-.0079029{col 73}{space 3} .0264219
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0277943{col 32}{space 2} .0119155{col 43}{space 1}    2.33{col 52}{space 3}0.024{col 60}{space 4} .0038096{col 73}{space 3} .0517789
{txt}{space 15}FL  {c |}{col 20}{res}{space 2} .0287426{col 32}{space 2} .0054691{col 43}{space 1}    5.26{col 52}{space 3}0.000{col 60}{space 4} .0177339{col 73}{space 3} .0397512
{txt}{space 15}GA  {c |}{col 20}{res}{space 2} .0031782{col 32}{space 2} .0065652{col 43}{space 1}    0.48{col 52}{space 3}0.631{col 60}{space 4}-.0100368{col 73}{space 3} .0163931
{txt}{space 15}IA  {c |}{col 20}{res}{space 2} .0208857{col 32}{space 2} .0060438{col 43}{space 1}    3.46{col 52}{space 3}0.001{col 60}{space 4}   .00872{col 73}{space 3} .0330513
{txt}{space 15}ID  {c |}{col 20}{res}{space 2} .0374575{col 32}{space 2} .0091052{col 43}{space 1}    4.11{col 52}{space 3}0.000{col 60}{space 4} .0191297{col 73}{space 3} .0557853
{txt}{space 15}IL  {c |}{col 20}{res}{space 2}  .010044{col 32}{space 2} .0093466{col 43}{space 1}    1.07{col 52}{space 3}0.288{col 60}{space 4}-.0087698{col 73}{space 3} .0288578
{txt}{space 15}IN  {c |}{col 20}{res}{space 2} .0126405{col 32}{space 2} .0117724{col 43}{space 1}    1.07{col 52}{space 3}0.289{col 60}{space 4}-.0110561{col 73}{space 3} .0363371
{txt}{space 15}KS  {c |}{col 20}{res}{space 2} .0048287{col 32}{space 2} .0046123{col 43}{space 1}    1.05{col 52}{space 3}0.301{col 60}{space 4}-.0044554{col 73}{space 3} .0141128
{txt}{space 15}KY  {c |}{col 20}{res}{space 2} .0096283{col 32}{space 2}  .009311{col 43}{space 1}    1.03{col 52}{space 3}0.307{col 60}{space 4}-.0091138{col 73}{space 3} .0283703
{txt}{space 15}LA  {c |}{col 20}{res}{space 2} .0031868{col 32}{space 2} .0035942{col 43}{space 1}    0.89{col 52}{space 3}0.380{col 60}{space 4}-.0040479{col 73}{space 3} .0104216
{txt}{space 15}MA  {c |}{col 20}{res}{space 2} .0127498{col 32}{space 2} .0120091{col 43}{space 1}    1.06{col 52}{space 3}0.294{col 60}{space 4}-.0114232{col 73}{space 3} .0369228
{txt}{space 15}MD  {c |}{col 20}{res}{space 2}-.0012857{col 32}{space 2} .0061162{col 43}{space 1}   -0.21{col 52}{space 3}0.834{col 60}{space 4} -.013597{col 73}{space 3} .0110256
{txt}{space 15}ME  {c |}{col 20}{res}{space 2} .0215479{col 32}{space 2} .0210109{col 43}{space 1}    1.03{col 52}{space 3}0.310{col 60}{space 4}-.0207448{col 73}{space 3} .0638407
{txt}{space 15}MI  {c |}{col 20}{res}{space 2} .0206631{col 32}{space 2}  .019229{col 43}{space 1}    1.07{col 52}{space 3}0.288{col 60}{space 4}-.0180429{col 73}{space 3} .0593692
{txt}{space 15}MN  {c |}{col 20}{res}{space 2} .0063255{col 32}{space 2} .0060103{col 43}{space 1}    1.05{col 52}{space 3}0.298{col 60}{space 4}-.0057726{col 73}{space 3} .0184235
{txt}{space 15}MO  {c |}{col 20}{res}{space 2} .0145556{col 32}{space 2} .0132476{col 43}{space 1}    1.10{col 52}{space 3}0.278{col 60}{space 4}-.0121104{col 73}{space 3} .0412216
{txt}{space 15}MS  {c |}{col 20}{res}{space 2} .0773553{col 32}{space 2} .0063077{col 43}{space 1}   12.26{col 52}{space 3}0.000{col 60}{space 4} .0646586{col 73}{space 3}  .090052
{txt}{space 15}MT  {c |}{col 20}{res}{space 2} .0878173{col 32}{space 2}  .009744{col 43}{space 1}    9.01{col 52}{space 3}0.000{col 60}{space 4} .0682036{col 73}{space 3} .1074309
{txt}{space 15}NC  {c |}{col 20}{res}{space 2} .0006711{col 32}{space 2} .0062722{col 43}{space 1}    0.11{col 52}{space 3}0.915{col 60}{space 4}-.0119542{col 73}{space 3} .0132965
{txt}{space 15}ND  {c |}{col 20}{res}{space 2}  .071342{col 32}{space 2} .0116935{col 43}{space 1}    6.10{col 52}{space 3}0.000{col 60}{space 4} .0478043{col 73}{space 3} .0948797
{txt}{space 15}NH  {c |}{col 20}{res}{space 2} .0232241{col 32}{space 2} .0230296{col 43}{space 1}    1.01{col 52}{space 3}0.319{col 60}{space 4}-.0231321{col 73}{space 3} .0695802
{txt}{space 15}NJ  {c |}{col 20}{res}{space 2} .0104269{col 32}{space 2} .0102126{col 43}{space 1}    1.02{col 52}{space 3}0.313{col 60}{space 4}  -.01013{col 73}{space 3} .0309838
{txt}{space 15}NM  {c |}{col 20}{res}{space 2}  .003201{col 32}{space 2} .0075591{col 43}{space 1}    0.42{col 52}{space 3}0.674{col 60}{space 4}-.0120148{col 73}{space 3} .0184168
{txt}{space 15}NV  {c |}{col 20}{res}{space 2}-.0066166{col 32}{space 2} .0132458{col 43}{space 1}   -0.50{col 52}{space 3}0.620{col 60}{space 4} -.033279{col 73}{space 3} .0200458
{txt}{space 15}NY  {c |}{col 20}{res}{space 2} .0157212{col 32}{space 2} .0148858{col 43}{space 1}    1.06{col 52}{space 3}0.296{col 60}{space 4}-.0142424{col 73}{space 3} .0456849
{txt}{space 15}OH  {c |}{col 20}{res}{space 2} .0156834{col 32}{space 2} .0145152{col 43}{space 1}    1.08{col 52}{space 3}0.286{col 60}{space 4}-.0135341{col 73}{space 3} .0449009
{txt}{space 15}OK  {c |}{col 20}{res}{space 2} .0081981{col 32}{space 2} .0084929{col 43}{space 1}    0.97{col 52}{space 3}0.339{col 60}{space 4}-.0088973{col 73}{space 3} .0252935
{txt}{space 15}OR  {c |}{col 20}{res}{space 2} .0055676{col 32}{space 2} .0058582{col 43}{space 1}    0.95{col 52}{space 3}0.347{col 60}{space 4}-.0062243{col 73}{space 3} .0173595
{txt}{space 15}PA  {c |}{col 20}{res}{space 2} .0170772{col 32}{space 2} .0162799{col 43}{space 1}    1.05{col 52}{space 3}0.300{col 60}{space 4}-.0156925{col 73}{space 3} .0498468
{txt}{space 15}RI  {c |}{col 20}{res}{space 2} .0127346{col 32}{space 2} .0124385{col 43}{space 1}    1.02{col 52}{space 3}0.311{col 60}{space 4}-.0123028{col 73}{space 3}  .037772
{txt}{space 15}SC  {c |}{col 20}{res}{space 2} .0452843{col 32}{space 2} .0136982{col 43}{space 1}    3.31{col 52}{space 3}0.002{col 60}{space 4} .0177114{col 73}{space 3} .0728573
{txt}{space 15}SD  {c |}{col 20}{res}{space 2} .0796793{col 32}{space 2} .0057059{col 43}{space 1}   13.96{col 52}{space 3}0.000{col 60}{space 4} .0681939{col 73}{space 3} .0911648
{txt}{space 15}TN  {c |}{col 20}{res}{space 2}  .003596{col 32}{space 2} .0054758{col 43}{space 1}    0.66{col 52}{space 3}0.515{col 60}{space 4}-.0074261{col 73}{space 3} .0146181
{txt}{space 15}TX  {c |}{col 20}{res}{space 2} .0066432{col 32}{space 2} .0067356{col 43}{space 1}    0.99{col 52}{space 3}0.329{col 60}{space 4}-.0069149{col 73}{space 3} .0202014
{txt}{space 15}UT  {c |}{col 20}{res}{space 2} -.001267{col 32}{space 2} .0105628{col 43}{space 1}   -0.12{col 52}{space 3}0.905{col 60}{space 4}-.0225288{col 73}{space 3} .0199949
{txt}{space 15}VA  {c |}{col 20}{res}{space 2}-.0030427{col 32}{space 2} .0058392{col 43}{space 1}   -0.52{col 52}{space 3}0.605{col 60}{space 4}-.0147965{col 73}{space 3} .0087111
{txt}{space 15}VT  {c |}{col 20}{res}{space 2} .0135274{col 32}{space 2} .0126561{col 43}{space 1}    1.07{col 52}{space 3}0.291{col 60}{space 4}-.0119481{col 73}{space 3} .0390028
{txt}{space 15}WA  {c |}{col 20}{res}{space 2} .0067455{col 32}{space 2} .0069881{col 43}{space 1}    0.97{col 52}{space 3}0.339{col 60}{space 4}-.0073208{col 73}{space 3} .0208117
{txt}{space 15}WI  {c |}{col 20}{res}{space 2} .0139817{col 32}{space 2} .0129654{col 43}{space 1}    1.08{col 52}{space 3}0.286{col 60}{space 4}-.0121162{col 73}{space 3} .0400796
{txt}{space 15}WV  {c |}{col 20}{res}{space 2} .0183614{col 32}{space 2} .0174493{col 43}{space 1}    1.05{col 52}{space 3}0.298{col 60}{space 4}-.0167622{col 73}{space 3} .0534851
{txt}{space 15}WY  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}-38.11889{col 32}{space 2} 15.07649{col 43}{space 1}   -2.53{col 52}{space 3}0.015{col 60}{space 4}-68.46629{col 73}{space 3}-7.771491
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_asimple_divided_gov.tex"'"':Table_asimple_divided_gov.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_asimple_divided_gov.txt", label"':seeout}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       830
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}F({res}   1{txt},{res}     46{txt}){col 67}= {res}      7.80
{txt}{col 49}Prob > F{col 67}= {res}    0.0076
{txt}{col 49}R-squared{col 67}= {res}    0.6091
{txt}{col 49}Adj R-squared{col 67}= {res}    0.5856
{txt}{col 49}Root MSE{col 67}= {res}    0.4353

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_a {c |}{col 20}{res}{space 2}  .144866{col 32}{space 2} .0518553{col 43}{space 1}    2.79{col 52}{space 3}0.008{col 60}{space 4} .0404867{col 73}{space 3} .2492453
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.301557{col 32}{space 2} .0175558{col 43}{space 1}   74.14{col 52}{space 3}0.000{col 60}{space 4} 1.266219{col 73}{space 3} 1.336895
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{stata `"shellout using `"Table_atrue_divided_gov_a.tex"'"':Table_atrue_divided_gov_a.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_a.txt", label"':seeout}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       830
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}F({res}  19{txt},{res}     46{txt}){col 67}= {res}      2.01
{txt}{col 49}Prob > F{col 67}= {res}    0.0275
{txt}{col 49}R-squared{col 67}= {res}    0.6328
{txt}{col 49}Adj R-squared{col 67}= {res}    0.6016
{txt}{col 49}Root MSE{col 67}= {res}    0.4268

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_a {c |}{col 20}{res}{space 2} .1488385{col 32}{space 2} .0520061{col 43}{space 1}    2.86{col 52}{space 3}0.006{col 60}{space 4} .0441556{col 73}{space 3} .2535213
{txt}{space 18} {c |}
{space 14}year {c |}
{space 13}1966  {c |}{col 20}{res}{space 2}   .03039{col 32}{space 2} .0361773{col 43}{space 1}    0.84{col 52}{space 3}0.405{col 60}{space 4}-.0424311{col 73}{space 3} .1032111
{txt}{space 13}1967  {c |}{col 20}{res}{space 2}  .101114{col 32}{space 2} .0635912{col 43}{space 1}    1.59{col 52}{space 3}0.119{col 60}{space 4}-.0268884{col 73}{space 3} .2291164
{txt}{space 13}1968  {c |}{col 20}{res}{space 2} .1267843{col 32}{space 2} .0797525{col 43}{space 1}    1.59{col 52}{space 3}0.119{col 60}{space 4}-.0337493{col 73}{space 3} .2873178
{txt}{space 13}1969  {c |}{col 20}{res}{space 2} .2639415{col 32}{space 2} .1121287{col 43}{space 1}    2.35{col 52}{space 3}0.023{col 60}{space 4} .0382381{col 73}{space 3} .4896449
{txt}{space 13}1970  {c |}{col 20}{res}{space 2} .2441464{col 32}{space 2} .1103185{col 43}{space 1}    2.21{col 52}{space 3}0.032{col 60}{space 4} .0220868{col 73}{space 3} .4662061
{txt}{space 13}1971  {c |}{col 20}{res}{space 2}  .181111{col 32}{space 2} .1119475{col 43}{space 1}    1.62{col 52}{space 3}0.113{col 60}{space 4}-.0442276{col 73}{space 3} .4064497
{txt}{space 13}1972  {c |}{col 20}{res}{space 2} .2026132{col 32}{space 2} .1187125{col 43}{space 1}    1.71{col 52}{space 3}0.095{col 60}{space 4}-.0363426{col 73}{space 3}  .441569
{txt}{space 13}1973  {c |}{col 20}{res}{space 2} .2662174{col 32}{space 2} .1200992{col 43}{space 1}    2.22{col 52}{space 3}0.032{col 60}{space 4} .0244703{col 73}{space 3} .5079645
{txt}{space 13}1974  {c |}{col 20}{res}{space 2} .2708405{col 32}{space 2} .1226509{col 43}{space 1}    2.21{col 52}{space 3}0.032{col 60}{space 4}  .023957{col 73}{space 3} .5177239
{txt}{space 13}1975  {c |}{col 20}{res}{space 2} .3193756{col 32}{space 2} .1295359{col 43}{space 1}    2.47{col 52}{space 3}0.017{col 60}{space 4} .0586334{col 73}{space 3} .5801179
{txt}{space 13}1976  {c |}{col 20}{res}{space 2} .3520554{col 32}{space 2} .1352937{col 43}{space 1}    2.60{col 52}{space 3}0.012{col 60}{space 4} .0797233{col 73}{space 3} .6243876
{txt}{space 13}1977  {c |}{col 20}{res}{space 2} .3378792{col 32}{space 2} .1347106{col 43}{space 1}    2.51{col 52}{space 3}0.016{col 60}{space 4} .0667208{col 73}{space 3} .6090375
{txt}{space 13}1978  {c |}{col 20}{res}{space 2} .2939259{col 32}{space 2} .1382498{col 43}{space 1}    2.13{col 52}{space 3}0.039{col 60}{space 4} .0156434{col 73}{space 3} .5722084
{txt}{space 13}1979  {c |}{col 20}{res}{space 2} .2824767{col 32}{space 2} .1403913{col 43}{space 1}    2.01{col 52}{space 3}0.050{col 60}{space 4}-.0001163{col 73}{space 3} .5650698
{txt}{space 13}1980  {c |}{col 20}{res}{space 2} .2970291{col 32}{space 2} .1468266{col 43}{space 1}    2.02{col 52}{space 3}0.049{col 60}{space 4} .0014825{col 73}{space 3} .5925756
{txt}{space 13}1981  {c |}{col 20}{res}{space 2}  .348367{col 32}{space 2} .1502464{col 43}{space 1}    2.32{col 52}{space 3}0.025{col 60}{space 4} .0459365{col 73}{space 3} .6507974
{txt}{space 13}1982  {c |}{col 20}{res}{space 2} .3180995{col 32}{space 2} .1504463{col 43}{space 1}    2.11{col 52}{space 3}0.040{col 60}{space 4} .0152668{col 73}{space 3} .6209322
{txt}{space 13}1983  {c |}{col 20}{res}{space 2} .3342552{col 32}{space 2} .1493111{col 43}{space 1}    2.24{col 52}{space 3}0.030{col 60}{space 4} .0337076{col 73}{space 3} .6348029
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 1.061495{col 32}{space 2} .1031699{col 43}{space 1}   10.29{col 52}{space 3}0.000{col 60}{space 4} .8538249{col 73}{space 3} 1.269165
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_atrue_divided_gov_a.tex"'"':Table_atrue_divided_gov_a.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_a.txt", label"':seeout}
{p 0 6 2}note: 50.state#c.year omitted because of collinearity{p_end}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       830
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}{help j_robustsingular##|_new:F(  23,     46)}{col 67}=          {res}.
{txt}{col 49}Prob > F{col 67}=          {res}.
{txt}{col 49}R-squared{col 67}= {res}    0.8391
{txt}{col 49}Adj R-squared{col 67}= {res}    0.8132
{txt}{col 49}Root MSE{col 67}= {res}    0.2833

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_a {c |}{col 20}{res}{space 2} .0815918{col 32}{space 2} .0453466{col 43}{space 1}    1.80{col 52}{space 3}0.079{col 60}{space 4}-.0096862{col 73}{space 3} .1728698
{txt}{space 10}ideociti {c |}{col 20}{res}{space 2} .6196044{col 32}{space 2} .2571517{col 43}{space 1}    2.41{col 52}{space 3}0.020{col 60}{space 4} .1019849{col 73}{space 3} 1.137224
{txt}{space 13}urban {c |}{col 20}{res}{space 2} 3.899107{col 32}{space 2} 8.214271{col 43}{space 1}    0.47{col 52}{space 3}0.637{col 60}{space 4}-12.63536{col 73}{space 3} 20.43358
{txt}{space 12}income {c |}{col 20}{res}{space 2} .0421625{col 32}{space 2} .0848739{col 43}{space 1}    0.50{col 52}{space 3}0.622{col 60}{space 4}-.1286798{col 73}{space 3} .2130048
{txt}{space 10}lfullemp {c |}{col 20}{res}{space 2} .2410466{col 32}{space 2}  .381701{col 43}{space 1}    0.63{col 52}{space 3}0.531{col 60}{space 4}-.5272778{col 73}{space 3} 1.009371
{txt}{space 18} {c |}
{space 14}year {c |}
{space 13}1966  {c |}{col 20}{res}{space 2}-.0227999{col 32}{space 2} .0695497{col 43}{space 1}   -0.33{col 52}{space 3}0.745{col 60}{space 4}-.1627961{col 73}{space 3} .1171964
{txt}{space 13}1967  {c |}{col 20}{res}{space 2}-.0453768{col 32}{space 2} .1239795{col 43}{space 1}   -0.37{col 52}{space 3}0.716{col 60}{space 4}-.2949346{col 73}{space 3}  .204181
{txt}{space 13}1968  {c |}{col 20}{res}{space 2}-.1110736{col 32}{space 2} .1884725{col 43}{space 1}   -0.59{col 52}{space 3}0.559{col 60}{space 4}-.4904491{col 73}{space 3} .2683018
{txt}{space 13}1969  {c |}{col 20}{res}{space 2}-.0391082{col 32}{space 2} .2301918{col 43}{space 1}   -0.17{col 52}{space 3}0.866{col 60}{space 4}-.5024602{col 73}{space 3} .4242438
{txt}{space 13}1970  {c |}{col 20}{res}{space 2}-.1096321{col 32}{space 2} .2793689{col 43}{space 1}   -0.39{col 52}{space 3}0.697{col 60}{space 4}-.6719725{col 73}{space 3} .4527084
{txt}{space 13}1971  {c |}{col 20}{res}{space 2}-.2157672{col 32}{space 2} .3168273{col 43}{space 1}   -0.68{col 52}{space 3}0.499{col 60}{space 4}-.8535075{col 73}{space 3}  .421973
{txt}{space 13}1972  {c |}{col 20}{res}{space 2} -.226196{col 32}{space 2} .3682598{col 43}{space 1}   -0.61{col 52}{space 3}0.542{col 60}{space 4}-.9674645{col 73}{space 3} .5150724
{txt}{space 13}1973  {c |}{col 20}{res}{space 2} -.269918{col 32}{space 2} .4191479{col 43}{space 1}   -0.64{col 52}{space 3}0.523{col 60}{space 4}-1.113619{col 73}{space 3}  .573783
{txt}{space 13}1974  {c |}{col 20}{res}{space 2}-.2849467{col 32}{space 2} .4256013{col 43}{space 1}   -0.67{col 52}{space 3}0.507{col 60}{space 4}-1.141638{col 73}{space 3} .5717443
{txt}{space 13}1975  {c |}{col 20}{res}{space 2}-.2794685{col 32}{space 2} .4639337{col 43}{space 1}   -0.60{col 52}{space 3}0.550{col 60}{space 4}-1.213319{col 73}{space 3} .6543816
{txt}{space 13}1976  {c |}{col 20}{res}{space 2}-.2661957{col 32}{space 2} .4982374{col 43}{space 1}   -0.53{col 52}{space 3}0.596{col 60}{space 4}-1.269096{col 73}{space 3} .7367042
{txt}{space 13}1977  {c |}{col 20}{res}{space 2}-.3187995{col 32}{space 2} .5333567{col 43}{space 1}   -0.60{col 52}{space 3}0.553{col 60}{space 4}-1.392391{col 73}{space 3} .7547918
{txt}{space 13}1978  {c |}{col 20}{res}{space 2} -.354735{col 32}{space 2} .5749418{col 43}{space 1}   -0.62{col 52}{space 3}0.540{col 60}{space 4}-1.512033{col 73}{space 3} .8025629
{txt}{space 13}1979  {c |}{col 20}{res}{space 2} -.399511{col 32}{space 2} .5938462{col 43}{space 1}   -0.67{col 52}{space 3}0.504{col 60}{space 4}-1.594862{col 73}{space 3} .7958394
{txt}{space 13}1980  {c |}{col 20}{res}{space 2}-.4341984{col 32}{space 2} .5936014{col 43}{space 1}   -0.73{col 52}{space 3}0.468{col 60}{space 4}-1.629056{col 73}{space 3} .7606593
{txt}{space 13}1981  {c |}{col 20}{res}{space 2}-.4430188{col 32}{space 2} .6170214{col 43}{space 1}   -0.72{col 52}{space 3}0.476{col 60}{space 4}-1.685019{col 73}{space 3} .7989809
{txt}{space 13}1982  {c |}{col 20}{res}{space 2}-.5214042{col 32}{space 2} .6374696{col 43}{space 1}   -0.82{col 52}{space 3}0.418{col 60}{space 4}-1.804564{col 73}{space 3} .7617555
{txt}{space 13}1983  {c |}{col 20}{res}{space 2}-.5680845{col 32}{space 2} .6677631{col 43}{space 1}   -0.85{col 52}{space 3}0.399{col 60}{space 4}-1.912222{col 73}{space 3} .7760529
{txt}{space 18} {c |}
{space 6}state#c.year {c |}
{space 15}AL  {c |}{col 20}{res}{space 2}-.0045033{col 32}{space 2} .0135246{col 43}{space 1}   -0.33{col 52}{space 3}0.741{col 60}{space 4}-.0317269{col 73}{space 3} .0227202
{txt}{space 15}AR  {c |}{col 20}{res}{space 2} .0996444{col 32}{space 2} .0095142{col 43}{space 1}   10.47{col 52}{space 3}0.000{col 60}{space 4} .0804932{col 73}{space 3} .1187956
{txt}{space 15}AZ  {c |}{col 20}{res}{space 2} .0838594{col 32}{space 2} .0207315{col 43}{space 1}    4.05{col 52}{space 3}0.000{col 60}{space 4} .0421291{col 73}{space 3} .1255898
{txt}{space 15}CA  {c |}{col 20}{res}{space 2} .0419435{col 32}{space 2} .0152736{col 43}{space 1}    2.75{col 52}{space 3}0.009{col 60}{space 4} .0111993{col 73}{space 3} .0726877
{txt}{space 15}CO  {c |}{col 20}{res}{space 2}-.0027627{col 32}{space 2} .0051421{col 43}{space 1}   -0.54{col 52}{space 3}0.594{col 60}{space 4}-.0131133{col 73}{space 3} .0075878
{txt}{space 15}CT  {c |}{col 20}{res}{space 2} .0714679{col 32}{space 2}  .020714{col 43}{space 1}    3.45{col 52}{space 3}0.001{col 60}{space 4} .0297727{col 73}{space 3}  .113163
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0310466{col 32}{space 2} .0255539{col 43}{space 1}    1.21{col 52}{space 3}0.231{col 60}{space 4}-.0203907{col 73}{space 3} .0824838
{txt}{space 15}FL  {c |}{col 20}{res}{space 2} .0836223{col 32}{space 2} .0101956{col 43}{space 1}    8.20{col 52}{space 3}0.000{col 60}{space 4} .0630996{col 73}{space 3} .1041449
{txt}{space 15}GA  {c |}{col 20}{res}{space 2}-.0841327{col 32}{space 2} .0135422{col 43}{space 1}   -6.21{col 52}{space 3}0.000{col 60}{space 4}-.1113917{col 73}{space 3}-.0568736
{txt}{space 15}IA  {c |}{col 20}{res}{space 2} .0508372{col 32}{space 2} .0130223{col 43}{space 1}    3.90{col 52}{space 3}0.000{col 60}{space 4} .0246247{col 73}{space 3} .0770498
{txt}{space 15}ID  {c |}{col 20}{res}{space 2} .1078624{col 32}{space 2} .0187999{col 43}{space 1}    5.74{col 52}{space 3}0.000{col 60}{space 4} .0700202{col 73}{space 3} .1457047
{txt}{space 15}IL  {c |}{col 20}{res}{space 2} .0135017{col 32}{space 2} .0216173{col 43}{space 1}    0.62{col 52}{space 3}0.535{col 60}{space 4}-.0300117{col 73}{space 3} .0570152
{txt}{space 15}IN  {c |}{col 20}{res}{space 2}-.0562339{col 32}{space 2} .0267914{col 43}{space 1}   -2.10{col 52}{space 3}0.041{col 60}{space 4}-.1101622{col 73}{space 3}-.0023056
{txt}{space 15}KS  {c |}{col 20}{res}{space 2}  .006689{col 32}{space 2} .0119477{col 43}{space 1}    0.56{col 52}{space 3}0.578{col 60}{space 4}-.0173605{col 73}{space 3} .0307386
{txt}{space 15}KY  {c |}{col 20}{res}{space 2} .0083278{col 32}{space 2} .0206937{col 43}{space 1}    0.40{col 52}{space 3}0.689{col 60}{space 4}-.0333264{col 73}{space 3}  .049982
{txt}{space 15}LA  {c |}{col 20}{res}{space 2}-.0003313{col 32}{space 2}  .007879{col 43}{space 1}   -0.04{col 52}{space 3}0.967{col 60}{space 4}-.0161909{col 73}{space 3} .0155282
{txt}{space 15}MA  {c |}{col 20}{res}{space 2} .0156544{col 32}{space 2} .0273951{col 43}{space 1}    0.57{col 52}{space 3}0.570{col 60}{space 4}-.0394891{col 73}{space 3} .0707978
{txt}{space 15}MD  {c |}{col 20}{res}{space 2}-.0052259{col 32}{space 2} .0126996{col 43}{space 1}   -0.41{col 52}{space 3}0.683{col 60}{space 4}-.0307888{col 73}{space 3} .0203369
{txt}{space 15}ME  {c |}{col 20}{res}{space 2}-.0407416{col 32}{space 2} .0468391{col 43}{space 1}   -0.87{col 52}{space 3}0.389{col 60}{space 4}-.1350239{col 73}{space 3} .0535408
{txt}{space 15}MI  {c |}{col 20}{res}{space 2} .0263899{col 32}{space 2} .0436222{col 43}{space 1}    0.60{col 52}{space 3}0.548{col 60}{space 4} -.061417{col 73}{space 3} .1141967
{txt}{space 15}MN  {c |}{col 20}{res}{space 2}-.0680088{col 32}{space 2} .0138038{col 43}{space 1}   -4.93{col 52}{space 3}0.000{col 60}{space 4}-.0957944{col 73}{space 3}-.0402232
{txt}{space 15}MO  {c |}{col 20}{res}{space 2} .0910466{col 32}{space 2} .0304464{col 43}{space 1}    2.99{col 52}{space 3}0.004{col 60}{space 4} .0297611{col 73}{space 3} .1523321
{txt}{space 15}MS  {c |}{col 20}{res}{space 2} .0695834{col 32}{space 2} .0118369{col 43}{space 1}    5.88{col 52}{space 3}0.000{col 60}{space 4}  .045757{col 73}{space 3} .0934098
{txt}{space 15}MT  {c |}{col 20}{res}{space 2} .1664447{col 32}{space 2} .0225221{col 43}{space 1}    7.39{col 52}{space 3}0.000{col 60}{space 4}   .12111{col 73}{space 3} .2117793
{txt}{space 15}NC  {c |}{col 20}{res}{space 2}-.0101456{col 32}{space 2}  .011913{col 43}{space 1}   -0.85{col 52}{space 3}0.399{col 60}{space 4}-.0341253{col 73}{space 3} .0138342
{txt}{space 15}ND  {c |}{col 20}{res}{space 2} .1285635{col 32}{space 2} .0238521{col 43}{space 1}    5.39{col 52}{space 3}0.000{col 60}{space 4} .0805517{col 73}{space 3} .1765752
{txt}{space 15}NH  {c |}{col 20}{res}{space 2} .0339805{col 32}{space 2} .0518247{col 43}{space 1}    0.66{col 52}{space 3}0.515{col 60}{space 4}-.0703372{col 73}{space 3} .1382981
{txt}{space 15}NJ  {c |}{col 20}{res}{space 2} .0424986{col 32}{space 2}  .022813{col 43}{space 1}    1.86{col 52}{space 3}0.069{col 60}{space 4}-.0034216{col 73}{space 3} .0884188
{txt}{space 15}NM  {c |}{col 20}{res}{space 2}-.0697442{col 32}{space 2} .0145251{col 43}{space 1}   -4.80{col 52}{space 3}0.000{col 60}{space 4}-.0989817{col 73}{space 3}-.0405068
{txt}{space 15}NV  {c |}{col 20}{res}{space 2}-.0133512{col 32}{space 2} .0273828{col 43}{space 1}   -0.49{col 52}{space 3}0.628{col 60}{space 4}  -.06847{col 73}{space 3} .0417676
{txt}{space 15}NY  {c |}{col 20}{res}{space 2}   .02196{col 32}{space 2} .0338788{col 43}{space 1}    0.65{col 52}{space 3}0.520{col 60}{space 4}-.0462345{col 73}{space 3} .0901545
{txt}{space 15}OH  {c |}{col 20}{res}{space 2} .0856601{col 32}{space 2} .0325433{col 43}{space 1}    2.63{col 52}{space 3}0.012{col 60}{space 4} .0201538{col 73}{space 3} .1511665
{txt}{space 15}OK  {c |}{col 20}{res}{space 2} .0085643{col 32}{space 2} .0186159{col 43}{space 1}    0.46{col 52}{space 3}0.648{col 60}{space 4}-.0289076{col 73}{space 3} .0460363
{txt}{space 15}OR  {c |}{col 20}{res}{space 2}-.0645452{col 32}{space 2} .0118659{col 43}{space 1}   -5.44{col 52}{space 3}0.000{col 60}{space 4}  -.08843{col 73}{space 3}-.0406604
{txt}{space 15}PA  {c |}{col 20}{res}{space 2} .0888912{col 32}{space 2} .0394211{col 43}{space 1}    2.25{col 52}{space 3}0.029{col 60}{space 4} .0095405{col 73}{space 3} .1682418
{txt}{space 15}RI  {c |}{col 20}{res}{space 2} -.007648{col 32}{space 2} .0272611{col 43}{space 1}   -0.28{col 52}{space 3}0.780{col 60}{space 4}-.0625216{col 73}{space 3} .0472257
{txt}{space 15}SC  {c |}{col 20}{res}{space 2} .0790581{col 32}{space 2} .0283869{col 43}{space 1}    2.79{col 52}{space 3}0.008{col 60}{space 4} .0219183{col 73}{space 3}  .136198
{txt}{space 15}SD  {c |}{col 20}{res}{space 2} .0829191{col 32}{space 2} .0120862{col 43}{space 1}    6.86{col 52}{space 3}0.000{col 60}{space 4} .0585908{col 73}{space 3} .1072475
{txt}{space 15}TN  {c |}{col 20}{res}{space 2} .0005884{col 32}{space 2}  .010892{col 43}{space 1}    0.05{col 52}{space 3}0.957{col 60}{space 4}-.0213361{col 73}{space 3} .0225129
{txt}{space 15}TX  {c |}{col 20}{res}{space 2} .0031514{col 32}{space 2} .0157956{col 43}{space 1}    0.20{col 52}{space 3}0.843{col 60}{space 4}-.0286434{col 73}{space 3} .0349462
{txt}{space 15}UT  {c |}{col 20}{res}{space 2}-.0128545{col 32}{space 2} .0208056{col 43}{space 1}   -0.62{col 52}{space 3}0.540{col 60}{space 4} -.054734{col 73}{space 3} .0290249
{txt}{space 15}VA  {c |}{col 20}{res}{space 2} -.011685{col 32}{space 2} .0115132{col 43}{space 1}   -1.01{col 52}{space 3}0.315{col 60}{space 4}-.0348598{col 73}{space 3} .0114898
{txt}{space 15}VT  {c |}{col 20}{res}{space 2} .0102762{col 32}{space 2} .0275807{col 43}{space 1}    0.37{col 52}{space 3}0.711{col 60}{space 4} -.045241{col 73}{space 3} .0657934
{txt}{space 15}WA  {c |}{col 20}{res}{space 2} .0113133{col 32}{space 2} .0151817{col 43}{space 1}    0.75{col 52}{space 3}0.460{col 60}{space 4}-.0192459{col 73}{space 3} .0418724
{txt}{space 15}WI  {c |}{col 20}{res}{space 2}-.0166234{col 32}{space 2} .0295714{col 43}{space 1}   -0.56{col 52}{space 3}0.577{col 60}{space 4}-.0761476{col 73}{space 3} .0429008
{txt}{space 15}WV  {c |}{col 20}{res}{space 2} .0247789{col 32}{space 2} .0397828{col 43}{space 1}    0.62{col 52}{space 3}0.536{col 60}{space 4}-.0552998{col 73}{space 3} .1048575
{txt}{space 15}WY  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}-49.22714{col 32}{space 2} 33.37075{col 43}{space 1}   -1.48{col 52}{space 3}0.147{col 60}{space 4} -116.399{col 73}{space 3}  17.9447
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_atrue_divided_gov_a.tex"'"':Table_atrue_divided_gov_a.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_a.txt", label"':seeout}

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -803.7917}  
Iteration 1:{space 3}log pseudolikelihood = {res:-413.36593}  
Iteration 2:{space 3}log pseudolikelihood = {res:-379.48338}  
Iteration 3:{space 3}log pseudolikelihood = {res:-372.56964}  
Iteration 4:{space 3}log pseudolikelihood = {res: -371.7139}  
Iteration 5:{space 3}log pseudolikelihood = {res:-371.50279}  
Iteration 6:{space 3}log pseudolikelihood = {res:-371.46034}  
Iteration 7:{space 3}log pseudolikelihood = {res:-371.45115}  
Iteration 8:{space 3}log pseudolikelihood = {res:-371.44907}  
Iteration 9:{space 3}log pseudolikelihood = {res:-371.44856}  
Iteration 10:{space 2}log pseudolikelihood = {res:-371.44846}  
Iteration 11:{space 2}log pseudolikelihood = {res:-371.44844}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       830
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(36)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-371.44844{txt}{col 49}Pseudo R2{col 67}= {res}    0.5379

{txt}{ralign 90:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}civil_service_reform_ipe{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}true_divided_gov_a {c |}{col 26}{res}{space 2}  .817549{col 38}{space 2} .2997618{col 49}{space 1}    2.73{col 58}{space 3}0.006{col 66}{space 4} .2300266{col 79}{space 3} 1.405071
{txt}{space 16}ideociti {c |}{col 26}{res}{space 2} 8.392407{col 38}{space 2}  2.83382{col 49}{space 1}    2.96{col 58}{space 3}0.003{col 66}{space 4} 2.838222{col 79}{space 3} 13.94659
{txt}{space 19}urban {c |}{col 26}{res}{space 2} 45.45105{col 38}{space 2} 28.63126{col 49}{space 1}    1.59{col 58}{space 3}0.112{col 66}{space 4} -10.6652{col 79}{space 3} 101.5673
{txt}{space 18}income {c |}{col 26}{res}{space 2}-.0828377{col 38}{space 2} .4352438{col 49}{space 1}   -0.19{col 58}{space 3}0.849{col 66}{space 4}-.9358998{col 79}{space 3} .7702245
{txt}{space 16}lfullemp {c |}{col 26}{res}{space 2}-2.730892{col 38}{space 2} 4.127554{col 49}{space 1}   -0.66{col 58}{space 3}0.508{col 66}{space 4}-10.82075{col 79}{space 3} 5.358965
{txt}{space 24} {c |}
{space 20}year {c |}
{space 19}1966  {c |}{col 26}{res}{space 2} .4111068{col 38}{space 2} .4193235{col 49}{space 1}    0.98{col 58}{space 3}0.327{col 66}{space 4}-.4107522{col 79}{space 3} 1.232966
{txt}{space 19}1967  {c |}{col 26}{res}{space 2} .6636947{col 38}{space 2} .6566065{col 49}{space 1}    1.01{col 58}{space 3}0.312{col 66}{space 4}-.6232304{col 79}{space 3}  1.95062
{txt}{space 19}1968  {c |}{col 26}{res}{space 2} .7415382{col 38}{space 2} .9741127{col 49}{space 1}    0.76{col 58}{space 3}0.447{col 66}{space 4}-1.167688{col 79}{space 3} 2.650764
{txt}{space 19}1969  {c |}{col 26}{res}{space 2}  1.29429{col 38}{space 2} 1.095712{col 49}{space 1}    1.18{col 58}{space 3}0.238{col 66}{space 4} -.853267{col 79}{space 3} 3.441846
{txt}{space 19}1970  {c |}{col 26}{res}{space 2} 1.332411{col 38}{space 2}  1.26447{col 49}{space 1}    1.05{col 58}{space 3}0.292{col 66}{space 4}-1.145904{col 79}{space 3} 3.810727
{txt}{space 19}1971  {c |}{col 26}{res}{space 2} .7763041{col 38}{space 2} 1.395459{col 49}{space 1}    0.56{col 58}{space 3}0.578{col 66}{space 4}-1.958744{col 79}{space 3} 3.511353
{txt}{space 19}1972  {c |}{col 26}{res}{space 2} 1.393307{col 38}{space 2} 1.765794{col 49}{space 1}    0.79{col 58}{space 3}0.430{col 66}{space 4}-2.067585{col 79}{space 3} 4.854199
{txt}{space 19}1973  {c |}{col 26}{res}{space 2}   1.3945{col 38}{space 2} 2.046733{col 49}{space 1}    0.68{col 58}{space 3}0.496{col 66}{space 4}-2.617024{col 79}{space 3} 5.406023
{txt}{space 19}1974  {c |}{col 26}{res}{space 2} 1.579927{col 38}{space 2} 2.116468{col 49}{space 1}    0.75{col 58}{space 3}0.455{col 66}{space 4}-2.568274{col 79}{space 3} 5.728128
{txt}{space 19}1975  {c |}{col 26}{res}{space 2} 1.612825{col 38}{space 2} 2.314038{col 49}{space 1}    0.70{col 58}{space 3}0.486{col 66}{space 4}-2.922606{col 79}{space 3} 6.148256
{txt}{space 19}1976  {c |}{col 26}{res}{space 2} 2.265345{col 38}{space 2} 2.368256{col 49}{space 1}    0.96{col 58}{space 3}0.339{col 66}{space 4} -2.37635{col 79}{space 3} 6.907041
{txt}{space 19}1977  {c |}{col 26}{res}{space 2} 2.403008{col 38}{space 2} 2.530893{col 49}{space 1}    0.95{col 58}{space 3}0.342{col 66}{space 4}-2.557452{col 79}{space 3} 7.363468
{txt}{space 19}1978  {c |}{col 26}{res}{space 2} 2.490903{col 38}{space 2} 2.690149{col 49}{space 1}    0.93{col 58}{space 3}0.354{col 66}{space 4}-2.781691{col 79}{space 3} 7.763498
{txt}{space 19}1979  {c |}{col 26}{res}{space 2} 2.337227{col 38}{space 2} 2.821025{col 49}{space 1}    0.83{col 58}{space 3}0.407{col 66}{space 4}-3.191881{col 79}{space 3} 7.866334
{txt}{space 19}1980  {c |}{col 26}{res}{space 2} 2.370744{col 38}{space 2} 2.773179{col 49}{space 1}    0.85{col 58}{space 3}0.393{col 66}{space 4}-3.064587{col 79}{space 3} 7.806076
{txt}{space 19}1981  {c |}{col 26}{res}{space 2} 2.614455{col 38}{space 2} 2.741151{col 49}{space 1}    0.95{col 58}{space 3}0.340{col 66}{space 4}-2.758103{col 79}{space 3} 7.987013
{txt}{space 19}1982  {c |}{col 26}{res}{space 2} 1.892448{col 38}{space 2}  2.71549{col 49}{space 1}    0.70{col 58}{space 3}0.486{col 66}{space 4}-3.429816{col 79}{space 3} 7.214711
{txt}{space 19}1983  {c |}{col 26}{res}{space 2} 1.839125{col 38}{space 2}  2.68738{col 49}{space 1}    0.68{col 58}{space 3}0.494{col 66}{space 4}-3.428042{col 79}{space 3} 7.106292
{txt}{space 24} {c |}
{space 19}state {c |}
{space 21}AR  {c |}{col 26}{res}{space 2}-15.45879{col 38}{space 2} 2.755329{col 49}{space 1}   -5.61{col 58}{space 3}0.000{col 66}{space 4}-20.85913{col 79}{space 3}-10.05844
{txt}{space 21}AZ  {c |}{col 26}{res}{space 2}-29.81638{col 38}{space 2} 7.115903{col 49}{space 1}   -4.19{col 58}{space 3}0.000{col 66}{space 4} -43.7633{col 79}{space 3}-15.86947
{txt}{space 21}CA  {c |}{col 26}{res}{space 2}-31.30166{col 38}{space 2} 9.279698{col 49}{space 1}   -3.37{col 58}{space 3}0.001{col 66}{space 4}-49.48953{col 79}{space 3}-13.11378
{txt}{space 21}CO  {c |}{col 26}{res}{space 2}-32.32872{col 38}{space 2} 5.924624{col 49}{space 1}   -5.46{col 58}{space 3}0.000{col 66}{space 4}-43.94077{col 79}{space 3}-20.71667
{txt}{space 21}CT  {c |}{col 26}{res}{space 2}-31.89502{col 38}{space 2} 5.572776{col 49}{space 1}   -5.72{col 58}{space 3}0.000{col 66}{space 4}-42.81746{col 79}{space 3}-20.97258
{txt}{space 21}DE  {c |}{col 26}{res}{space 2}-31.93888{col 38}{space 2}  6.65999{col 49}{space 1}   -4.80{col 58}{space 3}0.000{col 66}{space 4}-44.99222{col 79}{space 3}-18.88554
{txt}{space 21}FL  {c |}{col 26}{res}{space 2} -26.3847{col 38}{space 2} 6.264858{col 49}{space 1}   -4.21{col 58}{space 3}0.000{col 66}{space 4}-38.66359{col 79}{space 3} -14.1058
{txt}{space 21}GA  {c |}{col 26}{res}{space 2} -17.8673{col 38}{space 2} 1.789127{col 49}{space 1}   -9.99{col 58}{space 3}0.000{col 66}{space 4}-21.37393{col 79}{space 3}-14.36068
{txt}{space 21}IA  {c |}{col 26}{res}{space 2} -18.1413{col 38}{space 2} 1.976153{col 49}{space 1}   -9.18{col 58}{space 3}0.000{col 66}{space 4}-22.01449{col 79}{space 3}-14.26812
{txt}{space 21}ID  {c |}{col 26}{res}{space 2}-20.08638{col 38}{space 2}  5.18928{col 49}{space 1}   -3.87{col 58}{space 3}0.000{col 66}{space 4}-30.25718{col 79}{space 3}-9.915582
{txt}{space 21}IL  {c |}{col 26}{res}{space 2}-31.79614{col 38}{space 2} 6.679631{col 49}{space 1}   -4.76{col 58}{space 3}0.000{col 66}{space 4}-44.88798{col 79}{space 3} -18.7043
{txt}{space 21}IN  {c |}{col 26}{res}{space 2} -22.5406{col 38}{space 2} 2.059766{col 49}{space 1}  -10.94{col 58}{space 3}0.000{col 66}{space 4}-26.57766{col 79}{space 3}-18.50353
{txt}{space 21}KS  {c |}{col 26}{res}{space 2}-6.249206{col 38}{space 2}   2.9518{col 49}{space 1}   -2.12{col 58}{space 3}0.034{col 66}{space 4}-12.03463{col 79}{space 3}-.4637853
{txt}{space 21}KY  {c |}{col 26}{res}{space 2}-18.35264{col 38}{space 2} 2.825026{col 49}{space 1}   -6.50{col 58}{space 3}0.000{col 66}{space 4}-23.88959{col 79}{space 3}-12.81569
{txt}{space 21}LA  {c |}{col 26}{res}{space 2}-3.026833{col 38}{space 2} 2.759652{col 49}{space 1}   -1.10{col 58}{space 3}0.273{col 66}{space 4}-8.435651{col 79}{space 3} 2.381986
{txt}{space 21}MA  {c |}{col 26}{res}{space 2}-15.13594{col 38}{space 2} 6.943117{col 49}{space 1}   -2.18{col 58}{space 3}0.029{col 66}{space 4} -28.7442{col 79}{space 3} -1.52768
{txt}{space 21}MD  {c |}{col 26}{res}{space 2}-31.28455{col 38}{space 2} 5.191358{col 49}{space 1}   -6.03{col 58}{space 3}0.000{col 66}{space 4}-41.45943{col 79}{space 3}-21.10968
{txt}{space 21}ME  {c |}{col 26}{res}{space 2}-19.96797{col 38}{space 2}  4.58559{col 49}{space 1}   -4.35{col 58}{space 3}0.000{col 66}{space 4}-28.95556{col 79}{space 3}-10.98038
{txt}{space 21}MI  {c |}{col 26}{res}{space 2}-7.933689{col 38}{space 2} 4.483264{col 49}{space 1}   -1.77{col 58}{space 3}0.077{col 66}{space 4}-16.72073{col 79}{space 3} .8533479
{txt}{space 21}MN  {c |}{col 26}{res}{space 2}-24.94738{col 38}{space 2} 2.610219{col 49}{space 1}   -9.56{col 58}{space 3}0.000{col 66}{space 4}-30.06332{col 79}{space 3}-19.83145
{txt}{space 21}MO  {c |}{col 26}{res}{space 2}-24.18971{col 38}{space 2} 2.936515{col 49}{space 1}   -8.24{col 58}{space 3}0.000{col 66}{space 4}-29.94518{col 79}{space 3}-18.43425
{txt}{space 21}MS  {c |}{col 26}{res}{space 2} -17.5516{col 38}{space 2} 3.604764{col 49}{space 1}   -4.87{col 58}{space 3}0.000{col 66}{space 4}-24.61681{col 79}{space 3}-10.48639
{txt}{space 21}MT  {c |}{col 26}{res}{space 2}-24.97235{col 38}{space 2} 4.967473{col 49}{space 1}   -5.03{col 58}{space 3}0.000{col 66}{space 4}-34.70842{col 79}{space 3}-15.23628
{txt}{space 21}NC  {c |}{col 26}{res}{space 2} 7.608224{col 38}{space 2} 5.054647{col 49}{space 1}    1.51{col 58}{space 3}0.132{col 66}{space 4}-2.298702{col 79}{space 3} 17.51515
{txt}{space 21}ND  {c |}{col 26}{res}{space 2}-22.39832{col 38}{space 2} 6.297297{col 49}{space 1}   -3.56{col 58}{space 3}0.000{col 66}{space 4} -34.7408{col 79}{space 3}-10.05585
{txt}{space 21}NH  {c |}{col 26}{res}{space 2}-18.74318{col 38}{space 2} 5.663444{col 49}{space 1}   -3.31{col 58}{space 3}0.001{col 66}{space 4}-29.84333{col 79}{space 3}-7.643033
{txt}{space 21}NJ  {c |}{col 26}{res}{space 2}-36.10604{col 38}{space 2} 7.973453{col 49}{space 1}   -4.53{col 58}{space 3}0.000{col 66}{space 4}-51.73372{col 79}{space 3}-20.47836
{txt}{space 21}NM  {c |}{col 26}{res}{space 2}-25.82642{col 38}{space 2} 4.874719{col 49}{space 1}   -5.30{col 58}{space 3}0.000{col 66}{space 4} -35.3807{col 79}{space 3}-16.27215
{txt}{space 21}NV  {c |}{col 26}{res}{space 2}-14.99912{col 38}{space 2} 10.20202{col 49}{space 1}   -1.47{col 58}{space 3}0.142{col 66}{space 4}-34.99471{col 79}{space 3} 4.996462
{txt}{space 21}NY  {c |}{col 26}{res}{space 2}-32.08227{col 38}{space 2} 8.222166{col 49}{space 1}   -3.90{col 58}{space 3}0.000{col 66}{space 4}-48.19742{col 79}{space 3}-15.96712
{txt}{space 21}OH  {c |}{col 26}{res}{space 2}-26.20215{col 38}{space 2} 4.708967{col 49}{space 1}   -5.56{col 58}{space 3}0.000{col 66}{space 4}-35.43156{col 79}{space 3}-16.97275
{txt}{space 21}OK  {c |}{col 26}{res}{space 2}-4.951768{col 38}{space 2} 2.726513{col 49}{space 1}   -1.82{col 58}{space 3}0.069{col 66}{space 4}-10.29564{col 79}{space 3} .3920989
{txt}{space 21}OR  {c |}{col 26}{res}{space 2}-27.04276{col 38}{space 2} 3.121425{col 49}{space 1}   -8.66{col 58}{space 3}0.000{col 66}{space 4}-33.16064{col 79}{space 3}-20.92488
{txt}{space 21}PA  {c |}{col 26}{res}{space 2}-24.18325{col 38}{space 2} 5.133697{col 49}{space 1}   -4.71{col 58}{space 3}0.000{col 66}{space 4}-34.24511{col 79}{space 3}-14.12139
{txt}{space 21}RI  {c |}{col 26}{res}{space 2}-36.85471{col 38}{space 2} 9.714876{col 49}{space 1}   -3.79{col 58}{space 3}0.000{col 66}{space 4}-55.89552{col 79}{space 3}-17.81391
{txt}{space 21}SC  {c |}{col 26}{res}{space 2}-13.36742{col 38}{space 2} 2.682464{col 49}{space 1}   -4.98{col 58}{space 3}0.000{col 66}{space 4}-18.62495{col 79}{space 3}-8.109887
{txt}{space 21}SD  {c |}{col 26}{res}{space 2}-22.35339{col 38}{space 2} 6.209397{col 49}{space 1}   -3.60{col 58}{space 3}0.000{col 66}{space 4}-34.52359{col 79}{space 3} -10.1832
{txt}{space 21}TN  {c |}{col 26}{res}{space 2}-21.25435{col 38}{space 2} 1.526515{col 49}{space 1}  -13.92{col 58}{space 3}0.000{col 66}{space 4}-24.24626{col 79}{space 3}-18.26243
{txt}{space 21}TX  {c |}{col 26}{res}{space 2}-54.15406{col 38}{space 2} 6.383527{col 49}{space 1}   -8.48{col 58}{space 3}0.000{col 66}{space 4}-66.66555{col 79}{space 3}-41.64258
{txt}{space 21}UT  {c |}{col 26}{res}{space 2}-28.77744{col 38}{space 2} 7.746852{col 49}{space 1}   -3.71{col 58}{space 3}0.000{col 66}{space 4}-43.96099{col 79}{space 3}-13.59389
{txt}{space 21}VA  {c |}{col 26}{res}{space 2}-20.60796{col 38}{space 2} 2.561396{col 49}{space 1}   -8.05{col 58}{space 3}0.000{col 66}{space 4} -25.6282{col 79}{space 3}-15.58771
{txt}{space 21}VT  {c |}{col 26}{res}{space 2}-15.11414{col 38}{space 2} 8.497173{col 49}{space 1}   -1.78{col 58}{space 3}0.075{col 66}{space 4} -31.7683{col 79}{space 3}  1.54001
{txt}{space 21}WA  {c |}{col 26}{res}{space 2}-29.87631{col 38}{space 2} 3.999395{col 49}{space 1}   -7.47{col 58}{space 3}0.000{col 66}{space 4}-37.71498{col 79}{space 3}-22.03764
{txt}{space 21}WI  {c |}{col 26}{res}{space 2}-21.50072{col 38}{space 2} 2.245922{col 49}{space 1}   -9.57{col 58}{space 3}0.000{col 66}{space 4}-25.90265{col 79}{space 3} -17.0988
{txt}{space 21}WV  {c |}{col 26}{res}{space 2}-41.29384{col 38}{space 2} 6.065442{col 49}{space 1}   -6.81{col 58}{space 3}0.000{col 66}{space 4}-53.18189{col 79}{space 3} -29.4058
{txt}{space 21}WY  {c |}{col 26}{res}{space 2}-27.31728{col 38}{space 2} 7.572724{col 49}{space 1}   -3.61{col 58}{space 3}0.000{col 66}{space 4}-42.15955{col 79}{space 3}-12.47502
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}/cut1 {c |}{col 26}{res}{space 2}-22.45837{col 38}{space 2}  40.6996{col 66}{space 4}-102.2281{col 79}{space 3} 57.31138
{txt}{space 19}/cut2 {c |}{col 26}{res}{space 2}-17.69919{col 38}{space 2} 40.73176{col 66}{space 4}-97.53197{col 79}{space 3} 62.13359
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 188 observations completely determined.{txt}  Standard errors questionable.{p_end}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_atrue_divided_gov_a.tex"'"':Table_atrue_divided_gov_a.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_a.txt", label"':seeout}
{p 0 6 2}note: 50.state#c.year omitted because of collinearity{p_end}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       893
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}{help j_robustsingular##|_new:F(  22,     46)}{col 67}=          {res}.
{txt}{col 49}Prob > F{col 67}=          {res}.
{txt}{col 49}R-squared{col 67}= {res}    0.8484
{txt}{col 49}Adj R-squared{col 67}= {res}    0.8260
{txt}{col 49}Root MSE{col 67}= {res}    0.1250

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~m{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_a {c |}{col 20}{res}{space 2} .0320825{col 32}{space 2} .0162882{col 43}{space 1}    1.97{col 52}{space 3}0.055{col 60}{space 4}-.0007039{col 73}{space 3}  .064869
{txt}{space 10}ideociti {c |}{col 20}{res}{space 2} .0201327{col 32}{space 2} .1394906{col 43}{space 1}    0.14{col 52}{space 3}0.886{col 60}{space 4}-.2606474{col 73}{space 3} .3009128
{txt}{space 13}urban {c |}{col 20}{res}{space 2} 3.082339{col 32}{space 2} 3.699718{col 43}{space 1}    0.83{col 52}{space 3}0.409{col 60}{space 4}-4.364808{col 73}{space 3} 10.52949
{txt}{space 12}income {c |}{col 20}{res}{space 2} .0249534{col 32}{space 2} .0431785{col 43}{space 1}    0.58{col 52}{space 3}0.566{col 60}{space 4}-.0619605{col 73}{space 3} .1118672
{txt}{space 10}lfullemp {c |}{col 20}{res}{space 2}-.0019624{col 32}{space 2} .1381731{col 43}{space 1}   -0.01{col 52}{space 3}0.989{col 60}{space 4}-.2800904{col 73}{space 3} .2761656
{txt}{space 18} {c |}
{space 14}year {c |}
{space 13}1966  {c |}{col 20}{res}{space 2} .0039707{col 32}{space 2} .0380964{col 43}{space 1}    0.10{col 52}{space 3}0.917{col 60}{space 4}-.0727134{col 73}{space 3} .0806548
{txt}{space 13}1967  {c |}{col 20}{res}{space 2} .0062212{col 32}{space 2} .0496759{col 43}{space 1}    0.13{col 52}{space 3}0.901{col 60}{space 4}-.0937712{col 73}{space 3} .1062137
{txt}{space 13}1968  {c |}{col 20}{res}{space 2}-.0133902{col 32}{space 2}   .07836{col 43}{space 1}   -0.17{col 52}{space 3}0.865{col 60}{space 4}-.1711207{col 73}{space 3} .1443402
{txt}{space 13}1969  {c |}{col 20}{res}{space 2}-.0066858{col 32}{space 2}   .09559{col 43}{space 1}   -0.07{col 52}{space 3}0.945{col 60}{space 4}-.1990985{col 73}{space 3} .1857269
{txt}{space 13}1970  {c |}{col 20}{res}{space 2}-.0407881{col 32}{space 2}  .112423{col 43}{space 1}   -0.36{col 52}{space 3}0.718{col 60}{space 4}-.2670838{col 73}{space 3} .1855075
{txt}{space 13}1971  {c |}{col 20}{res}{space 2}-.0729503{col 32}{space 2} .1260445{col 43}{space 1}   -0.58{col 52}{space 3}0.566{col 60}{space 4}-.3266646{col 73}{space 3}  .180764
{txt}{space 13}1972  {c |}{col 20}{res}{space 2}-.1095636{col 32}{space 2} .1489787{col 43}{space 1}   -0.74{col 52}{space 3}0.466{col 60}{space 4}-.4094421{col 73}{space 3}  .190315
{txt}{space 13}1973  {c |}{col 20}{res}{space 2}-.1263303{col 32}{space 2} .1670492{col 43}{space 1}   -0.76{col 52}{space 3}0.453{col 60}{space 4}-.4625829{col 73}{space 3} .2099224
{txt}{space 13}1974  {c |}{col 20}{res}{space 2}-.1423168{col 32}{space 2} .1670329{col 43}{space 1}   -0.85{col 52}{space 3}0.399{col 60}{space 4}-.4785366{col 73}{space 3}  .193903
{txt}{space 13}1975  {c |}{col 20}{res}{space 2}-.1406734{col 32}{space 2} .1860087{col 43}{space 1}   -0.76{col 52}{space 3}0.453{col 60}{space 4}-.5150896{col 73}{space 3} .2337427
{txt}{space 13}1976  {c |}{col 20}{res}{space 2}-.1274715{col 32}{space 2} .2064129{col 43}{space 1}   -0.62{col 52}{space 3}0.540{col 60}{space 4}-.5429591{col 73}{space 3} .2880162
{txt}{space 13}1977  {c |}{col 20}{res}{space 2}-.1579061{col 32}{space 2} .2234511{col 43}{space 1}   -0.71{col 52}{space 3}0.483{col 60}{space 4}-.6076899{col 73}{space 3} .2918778
{txt}{space 13}1978  {c |}{col 20}{res}{space 2}-.1917207{col 32}{space 2} .2444227{col 43}{space 1}   -0.78{col 52}{space 3}0.437{col 60}{space 4} -.683718{col 73}{space 3} .3002767
{txt}{space 13}1979  {c |}{col 20}{res}{space 2}-.2148214{col 32}{space 2} .2516856{col 43}{space 1}   -0.85{col 52}{space 3}0.398{col 60}{space 4}-.7214382{col 73}{space 3} .2917954
{txt}{space 13}1980  {c |}{col 20}{res}{space 2}-.2276719{col 32}{space 2} .2479886{col 43}{space 1}   -0.92{col 52}{space 3}0.363{col 60}{space 4} -.726847{col 73}{space 3} .2715032
{txt}{space 13}1981  {c |}{col 20}{res}{space 2}-.2518711{col 32}{space 2} .2603536{col 43}{space 1}   -0.97{col 52}{space 3}0.338{col 60}{space 4}-.7759356{col 73}{space 3} .2721935
{txt}{space 13}1982  {c |}{col 20}{res}{space 2}-.2768174{col 32}{space 2} .2717235{col 43}{space 1}   -1.02{col 52}{space 3}0.314{col 60}{space 4}-.8237683{col 73}{space 3} .2701336
{txt}{space 13}1983  {c |}{col 20}{res}{space 2}-.3049765{col 32}{space 2} .2887191{col 43}{space 1}   -1.06{col 52}{space 3}0.296{col 60}{space 4} -.886138{col 73}{space 3}  .276185
{txt}{space 18} {c |}
{space 6}state#c.year {c |}
{space 15}AL  {c |}{col 20}{res}{space 2} .0067597{col 32}{space 2} .0058994{col 43}{space 1}    1.15{col 52}{space 3}0.258{col 60}{space 4}-.0051153{col 73}{space 3} .0186347
{txt}{space 15}AR  {c |}{col 20}{res}{space 2} .0563381{col 32}{space 2}  .004818{col 43}{space 1}   11.69{col 52}{space 3}0.000{col 60}{space 4} .0466398{col 73}{space 3} .0660363
{txt}{space 15}AZ  {c |}{col 20}{res}{space 2} .0381634{col 32}{space 2} .0099466{col 43}{space 1}    3.84{col 52}{space 3}0.000{col 60}{space 4}  .018142{col 73}{space 3} .0581848
{txt}{space 15}CA  {c |}{col 20}{res}{space 2} .0088755{col 32}{space 2} .0065085{col 43}{space 1}    1.36{col 52}{space 3}0.179{col 60}{space 4}-.0042255{col 73}{space 3} .0219765
{txt}{space 15}CO  {c |}{col 20}{res}{space 2} .0010412{col 32}{space 2} .0024399{col 43}{space 1}    0.43{col 52}{space 3}0.672{col 60}{space 4}-.0038701{col 73}{space 3} .0059525
{txt}{space 15}CT  {c |}{col 20}{res}{space 2}  .011697{col 32}{space 2} .0086784{col 43}{space 1}    1.35{col 52}{space 3}0.184{col 60}{space 4}-.0057717{col 73}{space 3} .0291657
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0283042{col 32}{space 2} .0118713{col 43}{space 1}    2.38{col 52}{space 3}0.021{col 60}{space 4} .0044084{col 73}{space 3} .0521999
{txt}{space 15}FL  {c |}{col 20}{res}{space 2} .0320472{col 32}{space 2} .0052378{col 43}{space 1}    6.12{col 52}{space 3}0.000{col 60}{space 4} .0215041{col 73}{space 3} .0425903
{txt}{space 15}GA  {c |}{col 20}{res}{space 2} .0049309{col 32}{space 2} .0064526{col 43}{space 1}    0.76{col 52}{space 3}0.449{col 60}{space 4}-.0080574{col 73}{space 3} .0179192
{txt}{space 15}IA  {c |}{col 20}{res}{space 2} .0222352{col 32}{space 2} .0059243{col 43}{space 1}    3.75{col 52}{space 3}0.000{col 60}{space 4} .0103103{col 73}{space 3} .0341601
{txt}{space 15}ID  {c |}{col 20}{res}{space 2} .0366842{col 32}{space 2} .0092055{col 43}{space 1}    3.99{col 52}{space 3}0.000{col 60}{space 4} .0181546{col 73}{space 3} .0552139
{txt}{space 15}IL  {c |}{col 20}{res}{space 2} .0110134{col 32}{space 2} .0092845{col 43}{space 1}    1.19{col 52}{space 3}0.242{col 60}{space 4}-.0076752{col 73}{space 3}  .029702
{txt}{space 15}IN  {c |}{col 20}{res}{space 2} .0139995{col 32}{space 2} .0116891{col 43}{space 1}    1.20{col 52}{space 3}0.237{col 60}{space 4}-.0095295{col 73}{space 3} .0375284
{txt}{space 15}KS  {c |}{col 20}{res}{space 2} .0048014{col 32}{space 2}  .004542{col 43}{space 1}    1.06{col 52}{space 3}0.296{col 60}{space 4}-.0043412{col 73}{space 3}  .013944
{txt}{space 15}KY  {c |}{col 20}{res}{space 2} .0108902{col 32}{space 2} .0092092{col 43}{space 1}    1.18{col 52}{space 3}0.243{col 60}{space 4}-.0076469{col 73}{space 3} .0294274
{txt}{space 15}LA  {c |}{col 20}{res}{space 2} .0047604{col 32}{space 2}  .003523{col 43}{space 1}    1.35{col 52}{space 3}0.183{col 60}{space 4}-.0023309{col 73}{space 3} .0118518
{txt}{space 15}MA  {c |}{col 20}{res}{space 2} .0145961{col 32}{space 2}  .011824{col 43}{space 1}    1.23{col 52}{space 3}0.223{col 60}{space 4}-.0092044{col 73}{space 3} .0383965
{txt}{space 15}MD  {c |}{col 20}{res}{space 2} .0007045{col 32}{space 2}  .005982{col 43}{space 1}    0.12{col 52}{space 3}0.907{col 60}{space 4}-.0113366{col 73}{space 3} .0127456
{txt}{space 15}ME  {c |}{col 20}{res}{space 2} .0224615{col 32}{space 2} .0208371{col 43}{space 1}    1.08{col 52}{space 3}0.287{col 60}{space 4}-.0194814{col 73}{space 3} .0644044
{txt}{space 15}MI  {c |}{col 20}{res}{space 2} .0208935{col 32}{space 2} .0192733{col 43}{space 1}    1.08{col 52}{space 3}0.284{col 60}{space 4}-.0179015{col 73}{space 3} .0596886
{txt}{space 15}MN  {c |}{col 20}{res}{space 2} .0075972{col 32}{space 2} .0058969{col 43}{space 1}    1.29{col 52}{space 3}0.204{col 60}{space 4}-.0042726{col 73}{space 3} .0194671
{txt}{space 15}MO  {c |}{col 20}{res}{space 2} .0149861{col 32}{space 2} .0132877{col 43}{space 1}    1.13{col 52}{space 3}0.265{col 60}{space 4}-.0117606{col 73}{space 3} .0417328
{txt}{space 15}MS  {c |}{col 20}{res}{space 2} .0794147{col 32}{space 2} .0061845{col 43}{space 1}   12.84{col 52}{space 3}0.000{col 60}{space 4}  .066966{col 73}{space 3} .0918633
{txt}{space 15}MT  {c |}{col 20}{res}{space 2} .0891199{col 32}{space 2} .0097088{col 43}{space 1}    9.18{col 52}{space 3}0.000{col 60}{space 4} .0695771{col 73}{space 3} .1086627
{txt}{space 15}NC  {c |}{col 20}{res}{space 2} .0026897{col 32}{space 2} .0061789{col 43}{space 1}    0.44{col 52}{space 3}0.665{col 60}{space 4}-.0097478{col 73}{space 3} .0151273
{txt}{space 15}ND  {c |}{col 20}{res}{space 2}  .074255{col 32}{space 2} .0116055{col 43}{space 1}    6.40{col 52}{space 3}0.000{col 60}{space 4} .0508944{col 73}{space 3} .0976156
{txt}{space 15}NH  {c |}{col 20}{res}{space 2} .0229046{col 32}{space 2} .0229905{col 43}{space 1}    1.00{col 52}{space 3}0.324{col 60}{space 4}-.0233729{col 73}{space 3} .0691821
{txt}{space 15}NJ  {c |}{col 20}{res}{space 2}   .01117{col 32}{space 2} .0101756{col 43}{space 1}    1.10{col 52}{space 3}0.278{col 60}{space 4}-.0093124{col 73}{space 3} .0316523
{txt}{space 15}NM  {c |}{col 20}{res}{space 2} .0061812{col 32}{space 2} .0071642{col 43}{space 1}    0.86{col 52}{space 3}0.393{col 60}{space 4}-.0082396{col 73}{space 3} .0206019
{txt}{space 15}NV  {c |}{col 20}{res}{space 2}-.0039751{col 32}{space 2} .0130463{col 43}{space 1}   -0.30{col 52}{space 3}0.762{col 60}{space 4}-.0302359{col 73}{space 3} .0222857
{txt}{space 15}NY  {c |}{col 20}{res}{space 2} .0158135{col 32}{space 2} .0147944{col 43}{space 1}    1.07{col 52}{space 3}0.291{col 60}{space 4}-.0139661{col 73}{space 3}  .045593
{txt}{space 15}OH  {c |}{col 20}{res}{space 2} .0151653{col 32}{space 2} .0145189{col 43}{space 1}    1.04{col 52}{space 3}0.302{col 60}{space 4}-.0140597{col 73}{space 3} .0443903
{txt}{space 15}OK  {c |}{col 20}{res}{space 2} .0093774{col 32}{space 2} .0082425{col 43}{space 1}    1.14{col 52}{space 3}0.261{col 60}{space 4}-.0072138{col 73}{space 3} .0259686
{txt}{space 15}OR  {c |}{col 20}{res}{space 2} .0077099{col 32}{space 2}  .005765{col 43}{space 1}    1.34{col 52}{space 3}0.188{col 60}{space 4}-.0038945{col 73}{space 3} .0193143
{txt}{space 15}PA  {c |}{col 20}{res}{space 2} .0181433{col 32}{space 2} .0163014{col 43}{space 1}    1.11{col 52}{space 3}0.271{col 60}{space 4}-.0146696{col 73}{space 3} .0509563
{txt}{space 15}RI  {c |}{col 20}{res}{space 2} .0139206{col 32}{space 2} .0122784{col 43}{space 1}    1.13{col 52}{space 3}0.263{col 60}{space 4}-.0107946{col 73}{space 3} .0386357
{txt}{space 15}SC  {c |}{col 20}{res}{space 2} .0479162{col 32}{space 2} .0135707{col 43}{space 1}    3.53{col 52}{space 3}0.001{col 60}{space 4} .0205999{col 73}{space 3} .0752325
{txt}{space 15}SD  {c |}{col 20}{res}{space 2} .0815348{col 32}{space 2}  .005484{col 43}{space 1}   14.87{col 52}{space 3}0.000{col 60}{space 4}  .070496{col 73}{space 3} .0925736
{txt}{space 15}TN  {c |}{col 20}{res}{space 2}    .0058{col 32}{space 2} .0052467{col 43}{space 1}    1.11{col 52}{space 3}0.275{col 60}{space 4} -.004761{col 73}{space 3}  .016361
{txt}{space 15}TX  {c |}{col 20}{res}{space 2} .0077734{col 32}{space 2} .0067926{col 43}{space 1}    1.14{col 52}{space 3}0.258{col 60}{space 4}-.0058994{col 73}{space 3} .0214463
{txt}{space 15}UT  {c |}{col 20}{res}{space 2}  .000252{col 32}{space 2} .0104482{col 43}{space 1}    0.02{col 52}{space 3}0.981{col 60}{space 4}-.0207791{col 73}{space 3}  .021283
{txt}{space 15}VA  {c |}{col 20}{res}{space 2}-.0010224{col 32}{space 2} .0057302{col 43}{space 1}   -0.18{col 52}{space 3}0.859{col 60}{space 4}-.0125568{col 73}{space 3} .0105119
{txt}{space 15}VT  {c |}{col 20}{res}{space 2} .0153741{col 32}{space 2}  .012537{col 43}{space 1}    1.23{col 52}{space 3}0.226{col 60}{space 4}-.0098616{col 73}{space 3} .0406098
{txt}{space 15}WA  {c |}{col 20}{res}{space 2}  .009471{col 32}{space 2} .0068174{col 43}{space 1}    1.39{col 52}{space 3}0.171{col 60}{space 4}-.0042517{col 73}{space 3} .0231936
{txt}{space 15}WI  {c |}{col 20}{res}{space 2} .0146397{col 32}{space 2}  .013019{col 43}{space 1}    1.12{col 52}{space 3}0.267{col 60}{space 4}-.0115662{col 73}{space 3} .0408456
{txt}{space 15}WV  {c |}{col 20}{res}{space 2} .0189408{col 32}{space 2} .0174081{col 43}{space 1}    1.09{col 52}{space 3}0.282{col 60}{space 4}-.0160999{col 73}{space 3} .0539815
{txt}{space 15}WY  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}-40.60718{col 32}{space 2} 14.91898{col 43}{space 1}   -2.72{col 52}{space 3}0.009{col 60}{space 4}-70.63754{col 73}{space 3}-10.57683
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_atrue_divided_gov_a.tex"'"':Table_atrue_divided_gov_a.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_a.txt", label"':seeout}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       830
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}F({res}   1{txt},{res}     46{txt}){col 67}= {res}      7.94
{txt}{col 49}Prob > F{col 67}= {res}    0.0071
{txt}{col 49}R-squared{col 67}= {res}    0.6092
{txt}{col 49}Adj R-squared{col 67}= {res}    0.5857
{txt}{col 49}Root MSE{col 67}= {res}    0.4352

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_e {c |}{col 20}{res}{space 2} .1468456{col 32}{space 2} .0521237{col 43}{space 1}    2.82{col 52}{space 3}0.007{col 60}{space 4}  .041926{col 73}{space 3} .2517652
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.298941{col 32}{space 2} .0183375{col 43}{space 1}   70.84{col 52}{space 3}0.000{col 60}{space 4}  1.26203{col 73}{space 3} 1.335853
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{stata `"shellout using `"Table_atrue_divided_gov_e.tex"'"':Table_atrue_divided_gov_e.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_e.txt", label"':seeout}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       830
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}F({res}  19{txt},{res}     46{txt}){col 67}= {res}      1.97
{txt}{col 49}Prob > F{col 67}= {res}    0.0309
{txt}{col 49}R-squared{col 67}= {res}    0.6332
{txt}{col 49}Adj R-squared{col 67}= {res}    0.6020
{txt}{col 49}Root MSE{col 67}= {res}    0.4266

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_e {c |}{col 20}{res}{space 2} .1532893{col 32}{space 2} .0524871{col 43}{space 1}    2.92{col 52}{space 3}0.005{col 60}{space 4} .0476381{col 73}{space 3} .2589404
{txt}{space 18} {c |}
{space 14}year {c |}
{space 13}1966  {c |}{col 20}{res}{space 2} .0304356{col 32}{space 2} .0362277{col 43}{space 1}    0.84{col 52}{space 3}0.405{col 60}{space 4} -.042487{col 73}{space 3} .1033582
{txt}{space 13}1967  {c |}{col 20}{res}{space 2} .1077816{col 32}{space 2} .0633268{col 43}{space 1}    1.70{col 52}{space 3}0.096{col 60}{space 4}-.0196886{col 73}{space 3} .2352519
{txt}{space 13}1968  {c |}{col 20}{res}{space 2} .1338164{col 32}{space 2} .0798665{col 43}{space 1}    1.68{col 52}{space 3}0.101{col 60}{space 4}-.0269466{col 73}{space 3} .2945795
{txt}{space 13}1969  {c |}{col 20}{res}{space 2}  .268029{col 32}{space 2} .1124627{col 43}{space 1}    2.38{col 52}{space 3}0.021{col 60}{space 4} .0416534{col 73}{space 3} .4944047
{txt}{space 13}1970  {c |}{col 20}{res}{space 2} .2474224{col 32}{space 2} .1103559{col 43}{space 1}    2.24{col 52}{space 3}0.030{col 60}{space 4} .0252875{col 73}{space 3} .4695573
{txt}{space 13}1971  {c |}{col 20}{res}{space 2} .1878919{col 32}{space 2} .1113633{col 43}{space 1}    1.69{col 52}{space 3}0.098{col 60}{space 4}-.0362708{col 73}{space 3} .4120546
{txt}{space 13}1972  {c |}{col 20}{res}{space 2} .2074536{col 32}{space 2} .1182627{col 43}{space 1}    1.75{col 52}{space 3}0.086{col 60}{space 4}-.0305969{col 73}{space 3} .4455041
{txt}{space 13}1973  {c |}{col 20}{res}{space 2} .2729983{col 32}{space 2} .1203539{col 43}{space 1}    2.27{col 52}{space 3}0.028{col 60}{space 4} .0307384{col 73}{space 3} .5152582
{txt}{space 13}1974  {c |}{col 20}{res}{space 2} .2772152{col 32}{space 2} .1233789{col 43}{space 1}    2.25{col 52}{space 3}0.029{col 60}{space 4} .0288664{col 73}{space 3}  .525564
{txt}{space 13}1975  {c |}{col 20}{res}{space 2} .3229318{col 32}{space 2} .1295222{col 43}{space 1}    2.49{col 52}{space 3}0.016{col 60}{space 4} .0622172{col 73}{space 3} .5836464
{txt}{space 13}1976  {c |}{col 20}{res}{space 2} .3557401{col 32}{space 2} .1354355{col 43}{space 1}    2.63{col 52}{space 3}0.012{col 60}{space 4} .0831227{col 73}{space 3} .6283576
{txt}{space 13}1977  {c |}{col 20}{res}{space 2} .3413385{col 32}{space 2} .1346564{col 43}{space 1}    2.53{col 52}{space 3}0.015{col 60}{space 4} .0702892{col 73}{space 3} .6123878
{txt}{space 13}1978  {c |}{col 20}{res}{space 2} .2988404{col 32}{space 2} .1382145{col 43}{space 1}    2.16{col 52}{space 3}0.036{col 60}{space 4} .0206291{col 73}{space 3} .5770518
{txt}{space 13}1979  {c |}{col 20}{res}{space 2}  .287049{col 32}{space 2} .1402896{col 43}{space 1}    2.05{col 52}{space 3}0.046{col 60}{space 4} .0046607{col 73}{space 3} .5694372
{txt}{space 13}1980  {c |}{col 20}{res}{space 2}  .301523{col 32}{space 2}  .146729{col 43}{space 1}    2.05{col 52}{space 3}0.046{col 60}{space 4} .0061728{col 73}{space 3} .5968733
{txt}{space 13}1981  {c |}{col 20}{res}{space 2} .3524518{col 32}{space 2} .1500082{col 43}{space 1}    2.35{col 52}{space 3}0.023{col 60}{space 4} .0505009{col 73}{space 3} .6544027
{txt}{space 13}1982  {c |}{col 20}{res}{space 2} .3213604{col 32}{space 2} .1497756{col 43}{space 1}    2.15{col 52}{space 3}0.037{col 60}{space 4} .0198776{col 73}{space 3} .6228431
{txt}{space 13}1983  {c |}{col 20}{res}{space 2} .3378344{col 32}{space 2}  .149079{col 43}{space 1}    2.27{col 52}{space 3}0.028{col 60}{space 4} .0377539{col 73}{space 3}  .637915
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 1.053681{col 32}{space 2} .1040568{col 43}{space 1}   10.13{col 52}{space 3}0.000{col 60}{space 4} .8442255{col 73}{space 3} 1.263137
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_atrue_divided_gov_e.tex"'"':Table_atrue_divided_gov_e.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_e.txt", label"':seeout}
{p 0 6 2}note: 50.state#c.year omitted because of collinearity{p_end}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       830
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}{help j_robustsingular##|_new:F(  23,     46)}{col 67}=          {res}.
{txt}{col 49}Prob > F{col 67}=          {res}.
{txt}{col 49}R-squared{col 67}= {res}    0.8390
{txt}{col 49}Adj R-squared{col 67}= {res}    0.8131
{txt}{col 49}Root MSE{col 67}= {res}    0.2833

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_e {c |}{col 20}{res}{space 2} .0806647{col 32}{space 2} .0461662{col 43}{space 1}    1.75{col 52}{space 3}0.087{col 60}{space 4} -.012263{col 73}{space 3} .1735924
{txt}{space 10}ideociti {c |}{col 20}{res}{space 2} .6152789{col 32}{space 2} .2570406{col 43}{space 1}    2.39{col 52}{space 3}0.021{col 60}{space 4}  .097883{col 73}{space 3} 1.132675
{txt}{space 13}urban {c |}{col 20}{res}{space 2}  3.81993{col 32}{space 2} 8.191314{col 43}{space 1}    0.47{col 52}{space 3}0.643{col 60}{space 4}-12.66833{col 73}{space 3} 20.30819
{txt}{space 12}income {c |}{col 20}{res}{space 2} .0411188{col 32}{space 2} .0849981{col 43}{space 1}    0.48{col 52}{space 3}0.631{col 60}{space 4}-.1299734{col 73}{space 3} .2122111
{txt}{space 10}lfullemp {c |}{col 20}{res}{space 2} .2253254{col 32}{space 2} .3848691{col 43}{space 1}    0.59{col 52}{space 3}0.561{col 60}{space 4}-.5493759{col 73}{space 3} 1.000027
{txt}{space 18} {c |}
{space 14}year {c |}
{space 13}1966  {c |}{col 20}{res}{space 2}-.0212113{col 32}{space 2} .0694828{col 43}{space 1}   -0.31{col 52}{space 3}0.762{col 60}{space 4} -.161073{col 73}{space 3} .1186503
{txt}{space 13}1967  {c |}{col 20}{res}{space 2}-.0385325{col 32}{space 2} .1239493{col 43}{space 1}   -0.31{col 52}{space 3}0.757{col 60}{space 4}-.2880295{col 73}{space 3} .2109645
{txt}{space 13}1968  {c |}{col 20}{res}{space 2}-.1020782{col 32}{space 2} .1885364{col 43}{space 1}   -0.54{col 52}{space 3}0.591{col 60}{space 4}-.4815824{col 73}{space 3} .2774259
{txt}{space 13}1969  {c |}{col 20}{res}{space 2}-.0305796{col 32}{space 2}  .230228{col 43}{space 1}   -0.13{col 52}{space 3}0.895{col 60}{space 4}-.4940045{col 73}{space 3} .4328452
{txt}{space 13}1970  {c |}{col 20}{res}{space 2}-.1001073{col 32}{space 2} .2790241{col 43}{space 1}   -0.36{col 52}{space 3}0.721{col 60}{space 4}-.6617536{col 73}{space 3} .4615391
{txt}{space 13}1971  {c |}{col 20}{res}{space 2}-.2029131{col 32}{space 2} .3160073{col 43}{space 1}   -0.64{col 52}{space 3}0.524{col 60}{space 4}-.8390029{col 73}{space 3} .4331766
{txt}{space 13}1972  {c |}{col 20}{res}{space 2}-.2126964{col 32}{space 2} .3674277{col 43}{space 1}   -0.58{col 52}{space 3}0.565{col 60}{space 4}  -.95229{col 73}{space 3} .5268973
{txt}{space 13}1973  {c |}{col 20}{res}{space 2}-.2539928{col 32}{space 2} .4191997{col 43}{space 1}   -0.61{col 52}{space 3}0.548{col 60}{space 4}-1.097798{col 73}{space 3} .5898123
{txt}{space 13}1974  {c |}{col 20}{res}{space 2}-.2684622{col 32}{space 2} .4258739{col 43}{space 1}   -0.63{col 52}{space 3}0.532{col 60}{space 4}-1.125702{col 73}{space 3} .5887775
{txt}{space 13}1975  {c |}{col 20}{res}{space 2}-.2638938{col 32}{space 2} .4637024{col 43}{space 1}   -0.57{col 52}{space 3}0.572{col 60}{space 4}-1.197278{col 73}{space 3} .6694908
{txt}{space 13}1976  {c |}{col 20}{res}{space 2}-.2498969{col 32}{space 2} .4984859{col 43}{space 1}   -0.50{col 52}{space 3}0.619{col 60}{space 4}-1.253297{col 73}{space 3} .7535031
{txt}{space 13}1977  {c |}{col 20}{res}{space 2}-.3014823{col 32}{space 2} .5334445{col 43}{space 1}   -0.57{col 52}{space 3}0.575{col 60}{space 4} -1.37525{col 73}{space 3} .7722857
{txt}{space 13}1978  {c |}{col 20}{res}{space 2}-.3355811{col 32}{space 2} .5753082{col 43}{space 1}   -0.58{col 52}{space 3}0.563{col 60}{space 4}-1.493616{col 73}{space 3} .8224543
{txt}{space 13}1979  {c |}{col 20}{res}{space 2}-.3794077{col 32}{space 2} .5939207{col 43}{space 1}   -0.64{col 52}{space 3}0.526{col 60}{space 4}-1.574908{col 73}{space 3} .8160927
{txt}{space 13}1980  {c |}{col 20}{res}{space 2} -.414138{col 32}{space 2} .5932047{col 43}{space 1}   -0.70{col 52}{space 3}0.489{col 60}{space 4}-1.608197{col 73}{space 3} .7799212
{txt}{space 13}1981  {c |}{col 20}{res}{space 2}-.4228909{col 32}{space 2} .6162228{col 43}{space 1}   -0.69{col 52}{space 3}0.496{col 60}{space 4}-1.663283{col 73}{space 3} .8175012
{txt}{space 13}1982  {c |}{col 20}{res}{space 2}-.5016877{col 32}{space 2} .6359003{col 43}{space 1}   -0.79{col 52}{space 3}0.434{col 60}{space 4}-1.781689{col 73}{space 3} .7783131
{txt}{space 13}1983  {c |}{col 20}{res}{space 2}-.5478835{col 32}{space 2} .6668654{col 43}{space 1}   -0.82{col 52}{space 3}0.416{col 60}{space 4}-1.890214{col 73}{space 3} .7944468
{txt}{space 18} {c |}
{space 6}state#c.year {c |}
{space 15}AL  {c |}{col 20}{res}{space 2}-.0044348{col 32}{space 2} .0135549{col 43}{space 1}   -0.33{col 52}{space 3}0.745{col 60}{space 4}-.0317194{col 73}{space 3} .0228497
{txt}{space 15}AR  {c |}{col 20}{res}{space 2} .0996402{col 32}{space 2} .0095324{col 43}{space 1}   10.45{col 52}{space 3}0.000{col 60}{space 4} .0804525{col 73}{space 3} .1188279
{txt}{space 15}AZ  {c |}{col 20}{res}{space 2} .0841594{col 32}{space 2} .0205903{col 43}{space 1}    4.09{col 52}{space 3}0.000{col 60}{space 4} .0427133{col 73}{space 3} .1256054
{txt}{space 15}CA  {c |}{col 20}{res}{space 2} .0416391{col 32}{space 2} .0151819{col 43}{space 1}    2.74{col 52}{space 3}0.009{col 60}{space 4} .0110795{col 73}{space 3} .0721988
{txt}{space 15}CO  {c |}{col 20}{res}{space 2}  -.00287{col 32}{space 2}   .00518{col 43}{space 1}   -0.55{col 52}{space 3}0.582{col 60}{space 4}-.0132969{col 73}{space 3} .0075568
{txt}{space 15}CT  {c |}{col 20}{res}{space 2} .0710978{col 32}{space 2} .0205337{col 43}{space 1}    3.46{col 52}{space 3}0.001{col 60}{space 4} .0297655{col 73}{space 3} .1124301
{txt}{space 15}DE  {c |}{col 20}{res}{space 2}  .030694{col 32}{space 2} .0255096{col 43}{space 1}    1.20{col 52}{space 3}0.235{col 60}{space 4}-.0206542{col 73}{space 3} .0820422
{txt}{space 15}FL  {c |}{col 20}{res}{space 2} .0837806{col 32}{space 2} .0103311{col 43}{space 1}    8.11{col 52}{space 3}0.000{col 60}{space 4} .0629852{col 73}{space 3}  .104576
{txt}{space 15}GA  {c |}{col 20}{res}{space 2} -.083979{col 32}{space 2} .0135946{col 43}{space 1}   -6.18{col 52}{space 3}0.000{col 60}{space 4}-.1113435{col 73}{space 3}-.0566145
{txt}{space 15}IA  {c |}{col 20}{res}{space 2} .0505177{col 32}{space 2}  .013004{col 43}{space 1}    3.88{col 52}{space 3}0.000{col 60}{space 4} .0243421{col 73}{space 3} .0766933
{txt}{space 15}ID  {c |}{col 20}{res}{space 2} .1075931{col 32}{space 2} .0188089{col 43}{space 1}    5.72{col 52}{space 3}0.000{col 60}{space 4} .0697326{col 73}{space 3} .1454535
{txt}{space 15}IL  {c |}{col 20}{res}{space 2} .0129498{col 32}{space 2} .0215199{col 43}{space 1}    0.60{col 52}{space 3}0.550{col 60}{space 4}-.0303676{col 73}{space 3} .0562671
{txt}{space 15}IN  {c |}{col 20}{res}{space 2}-.0568504{col 32}{space 2} .0266615{col 43}{space 1}   -2.13{col 52}{space 3}0.038{col 60}{space 4}-.1105172{col 73}{space 3}-.0031836
{txt}{space 15}KS  {c |}{col 20}{res}{space 2} .0065501{col 32}{space 2} .0119347{col 43}{space 1}    0.55{col 52}{space 3}0.586{col 60}{space 4}-.0174733{col 73}{space 3} .0305734
{txt}{space 15}KY  {c |}{col 20}{res}{space 2} .0081301{col 32}{space 2} .0206354{col 43}{space 1}    0.39{col 52}{space 3}0.695{col 60}{space 4}-.0334068{col 73}{space 3}  .049667
{txt}{space 15}LA  {c |}{col 20}{res}{space 2}-.0003915{col 32}{space 2} .0078745{col 43}{space 1}   -0.05{col 52}{space 3}0.961{col 60}{space 4} -.016242{col 73}{space 3}  .015459
{txt}{space 15}MA  {c |}{col 20}{res}{space 2} .0151858{col 32}{space 2} .0272397{col 43}{space 1}    0.56{col 52}{space 3}0.580{col 60}{space 4}-.0396448{col 73}{space 3} .0700164
{txt}{space 15}MD  {c |}{col 20}{res}{space 2}-.0049725{col 32}{space 2} .0127802{col 43}{space 1}   -0.39{col 52}{space 3}0.699{col 60}{space 4}-.0306976{col 73}{space 3} .0207526
{txt}{space 15}ME  {c |}{col 20}{res}{space 2}-.0415518{col 32}{space 2} .0466035{col 43}{space 1}   -0.89{col 52}{space 3}0.377{col 60}{space 4}-.1353598{col 73}{space 3} .0522563
{txt}{space 15}MI  {c |}{col 20}{res}{space 2} .0256895{col 32}{space 2} .0434584{col 43}{space 1}    0.59{col 52}{space 3}0.557{col 60}{space 4}-.0617876{col 73}{space 3} .1131667
{txt}{space 15}MN  {c |}{col 20}{res}{space 2}-.0683531{col 32}{space 2} .0137271{col 43}{space 1}   -4.98{col 52}{space 3}0.000{col 60}{space 4}-.0959843{col 73}{space 3}-.0407219
{txt}{space 15}MO  {c |}{col 20}{res}{space 2} .0905418{col 32}{space 2} .0303368{col 43}{space 1}    2.98{col 52}{space 3}0.005{col 60}{space 4} .0294769{col 73}{space 3} .1516067
{txt}{space 15}MS  {c |}{col 20}{res}{space 2} .0696271{col 32}{space 2} .0118574{col 43}{space 1}    5.87{col 52}{space 3}0.000{col 60}{space 4} .0457593{col 73}{space 3} .0934949
{txt}{space 15}MT  {c |}{col 20}{res}{space 2} .1660291{col 32}{space 2} .0224052{col 43}{space 1}    7.41{col 52}{space 3}0.000{col 60}{space 4} .1209297{col 73}{space 3} .2111285
{txt}{space 15}NC  {c |}{col 20}{res}{space 2}-.0100617{col 32}{space 2} .0119326{col 43}{space 1}   -0.84{col 52}{space 3}0.403{col 60}{space 4}-.0340808{col 73}{space 3} .0139575
{txt}{space 15}ND  {c |}{col 20}{res}{space 2} .1285958{col 32}{space 2}  .023855{col 43}{space 1}    5.39{col 52}{space 3}0.000{col 60}{space 4} .0805782{col 73}{space 3} .1766134
{txt}{space 15}NH  {c |}{col 20}{res}{space 2} .0333601{col 32}{space 2} .0516294{col 43}{space 1}    0.65{col 52}{space 3}0.521{col 60}{space 4}-.0705645{col 73}{space 3} .1372847
{txt}{space 15}NJ  {c |}{col 20}{res}{space 2} .0423766{col 32}{space 2} .0227682{col 43}{space 1}    1.86{col 52}{space 3}0.069{col 60}{space 4}-.0034534{col 73}{space 3} .0882066
{txt}{space 15}NM  {c |}{col 20}{res}{space 2}-.0696981{col 32}{space 2} .0146489{col 43}{space 1}   -4.76{col 52}{space 3}0.000{col 60}{space 4}-.0991848{col 73}{space 3}-.0402115
{txt}{space 15}NV  {c |}{col 20}{res}{space 2} -.012948{col 32}{space 2} .0273618{col 43}{space 1}   -0.47{col 52}{space 3}0.638{col 60}{space 4}-.0680244{col 73}{space 3} .0421284
{txt}{space 15}NY  {c |}{col 20}{res}{space 2} .0212959{col 32}{space 2}   .03378{col 43}{space 1}    0.63{col 52}{space 3}0.532{col 60}{space 4}-.0466998{col 73}{space 3} .0892915
{txt}{space 15}OH  {c |}{col 20}{res}{space 2}  .085216{col 32}{space 2} .0324706{col 43}{space 1}    2.62{col 52}{space 3}0.012{col 60}{space 4} .0198561{col 73}{space 3} .1505758
{txt}{space 15}OK  {c |}{col 20}{res}{space 2}   .00845{col 32}{space 2} .0185682{col 43}{space 1}    0.46{col 52}{space 3}0.651{col 60}{space 4}-.0289257{col 73}{space 3} .0458258
{txt}{space 15}OR  {c |}{col 20}{res}{space 2}-.0648774{col 32}{space 2} .0117484{col 43}{space 1}   -5.52{col 52}{space 3}0.000{col 60}{space 4}-.0885258{col 73}{space 3} -.041229
{txt}{space 15}PA  {c |}{col 20}{res}{space 2} .0880248{col 32}{space 2} .0391748{col 43}{space 1}    2.25{col 52}{space 3}0.029{col 60}{space 4}   .00917{col 73}{space 3} .1668797
{txt}{space 15}RI  {c |}{col 20}{res}{space 2}-.0068497{col 32}{space 2} .0272266{col 43}{space 1}   -0.25{col 52}{space 3}0.802{col 60}{space 4}-.0616541{col 73}{space 3} .0479547
{txt}{space 15}SC  {c |}{col 20}{res}{space 2} .0796505{col 32}{space 2} .0283393{col 43}{space 1}    2.81{col 52}{space 3}0.007{col 60}{space 4} .0226065{col 73}{space 3} .1366944
{txt}{space 15}SD  {c |}{col 20}{res}{space 2} .0825309{col 32}{space 2} .0121127{col 43}{space 1}    6.81{col 52}{space 3}0.000{col 60}{space 4} .0581494{col 73}{space 3} .1069124
{txt}{space 15}TN  {c |}{col 20}{res}{space 2} .0004958{col 32}{space 2}  .010899{col 43}{space 1}    0.05{col 52}{space 3}0.964{col 60}{space 4}-.0214429{col 73}{space 3} .0224344
{txt}{space 15}TX  {c |}{col 20}{res}{space 2} .0031954{col 32}{space 2} .0158213{col 43}{space 1}    0.20{col 52}{space 3}0.841{col 60}{space 4}-.0286511{col 73}{space 3}  .035042
{txt}{space 15}UT  {c |}{col 20}{res}{space 2}-.0127015{col 32}{space 2} .0207919{col 43}{space 1}   -0.61{col 52}{space 3}0.544{col 60}{space 4}-.0545534{col 73}{space 3} .0291503
{txt}{space 15}VA  {c |}{col 20}{res}{space 2}-.0114938{col 32}{space 2} .0115474{col 43}{space 1}   -1.00{col 52}{space 3}0.325{col 60}{space 4}-.0347375{col 73}{space 3} .0117499
{txt}{space 15}VT  {c |}{col 20}{res}{space 2} .0098123{col 32}{space 2}  .027417{col 43}{space 1}    0.36{col 52}{space 3}0.722{col 60}{space 4}-.0453753{col 73}{space 3}     .065
{txt}{space 15}WA  {c |}{col 20}{res}{space 2} .0110598{col 32}{space 2} .0151089{col 43}{space 1}    0.73{col 52}{space 3}0.468{col 60}{space 4}-.0193529{col 73}{space 3} .0414724
{txt}{space 15}WI  {c |}{col 20}{res}{space 2}-.0171225{col 32}{space 2} .0294285{col 43}{space 1}   -0.58{col 52}{space 3}0.564{col 60}{space 4}-.0763589{col 73}{space 3} .0421139
{txt}{space 15}WV  {c |}{col 20}{res}{space 2} .0240843{col 32}{space 2} .0395963{col 43}{space 1}    0.61{col 52}{space 3}0.546{col 60}{space 4} -.055619{col 73}{space 3} .1037875
{txt}{space 15}WY  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}-48.65403{col 32}{space 2}  33.2225{col 43}{space 1}   -1.46{col 52}{space 3}0.150{col 60}{space 4}-115.5275{col 73}{space 3}  18.2194
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_atrue_divided_gov_e.tex"'"':Table_atrue_divided_gov_e.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_e.txt", label"':seeout}

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -803.7917}  
Iteration 1:{space 3}log pseudolikelihood = {res:-413.18526}  
Iteration 2:{space 3}log pseudolikelihood = {res:-379.28382}  
Iteration 3:{space 3}log pseudolikelihood = {res:-372.35904}  
Iteration 4:{space 3}log pseudolikelihood = {res:-371.50111}  
Iteration 5:{space 3}log pseudolikelihood = {res:-371.28971}  
Iteration 6:{space 3}log pseudolikelihood = {res:-371.24711}  
Iteration 7:{space 3}log pseudolikelihood = {res: -371.2379}  
Iteration 8:{space 3}log pseudolikelihood = {res:-371.23583}  
Iteration 9:{space 3}log pseudolikelihood = {res:-371.23531}  
Iteration 10:{space 2}log pseudolikelihood = {res:-371.23521}  
Iteration 11:{space 2}log pseudolikelihood = {res:-371.23519}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}       830
{txt}{col 49}{help j_robustsingular##|_new:Wald chi2(35)}{col 67}=          {res}.
{txt}{col 49}Prob > chi2{col 67}=          {res}.
{txt}Log pseudolikelihood = {res}-371.23519{txt}{col 49}Pseudo R2{col 67}= {res}    0.5381

{txt}{ralign 90:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}civil_service_reform_ipe{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}true_divided_gov_e {c |}{col 26}{res}{space 2} .8409652{col 38}{space 2} .3054586{col 49}{space 1}    2.75{col 58}{space 3}0.006{col 66}{space 4} .2422772{col 79}{space 3} 1.439653
{txt}{space 16}ideociti {c |}{col 26}{res}{space 2} 8.347214{col 38}{space 2} 2.827022{col 49}{space 1}    2.95{col 58}{space 3}0.003{col 66}{space 4} 2.806353{col 79}{space 3} 13.88807
{txt}{space 19}urban {c |}{col 26}{res}{space 2}  45.7199{col 38}{space 2} 28.69135{col 49}{space 1}    1.59{col 58}{space 3}0.111{col 66}{space 4}-10.51411{col 79}{space 3} 101.9539
{txt}{space 18}income {c |}{col 26}{res}{space 2} -.097913{col 38}{space 2} .4327571{col 49}{space 1}   -0.23{col 58}{space 3}0.821{col 66}{space 4}-.9461013{col 79}{space 3} .7502752
{txt}{space 16}lfullemp {c |}{col 26}{res}{space 2}-2.833818{col 38}{space 2} 4.137807{col 49}{space 1}   -0.68{col 58}{space 3}0.493{col 66}{space 4}-10.94377{col 79}{space 3} 5.276135
{txt}{space 24} {c |}
{space 20}year {c |}
{space 19}1966  {c |}{col 26}{res}{space 2} .4229329{col 38}{space 2} .4210093{col 49}{space 1}    1.00{col 58}{space 3}0.315{col 66}{space 4}-.4022301{col 79}{space 3} 1.248096
{txt}{space 19}1967  {c |}{col 26}{res}{space 2} .7419163{col 38}{space 2} .6666559{col 49}{space 1}    1.11{col 58}{space 3}0.266{col 66}{space 4}-.5647052{col 79}{space 3} 2.048538
{txt}{space 19}1968  {c |}{col 26}{res}{space 2} .8398035{col 38}{space 2} .9885293{col 49}{space 1}    0.85{col 58}{space 3}0.396{col 66}{space 4}-1.097678{col 79}{space 3} 2.777285
{txt}{space 19}1969  {c |}{col 26}{res}{space 2} 1.366893{col 38}{space 2} 1.113819{col 49}{space 1}    1.23{col 58}{space 3}0.220{col 66}{space 4}-.8161516{col 79}{space 3} 3.549937
{txt}{space 19}1970  {c |}{col 26}{res}{space 2} 1.405429{col 38}{space 2} 1.280444{col 49}{space 1}    1.10{col 58}{space 3}0.272{col 66}{space 4}-1.104195{col 79}{space 3} 3.915052
{txt}{space 19}1971  {c |}{col 26}{res}{space 2} .8903748{col 38}{space 2} 1.406963{col 49}{space 1}    0.63{col 58}{space 3}0.527{col 66}{space 4}-1.867222{col 79}{space 3} 3.647971
{txt}{space 19}1972  {c |}{col 26}{res}{space 2} 1.502805{col 38}{space 2} 1.775614{col 49}{space 1}    0.85{col 58}{space 3}0.397{col 66}{space 4}-1.977333{col 79}{space 3} 4.982944
{txt}{space 19}1973  {c |}{col 26}{res}{space 2} 1.535136{col 38}{space 2} 2.061967{col 49}{space 1}    0.74{col 58}{space 3}0.457{col 66}{space 4}-2.506244{col 79}{space 3} 5.576516
{txt}{space 19}1974  {c |}{col 26}{res}{space 2} 1.719032{col 38}{space 2} 2.138808{col 49}{space 1}    0.80{col 58}{space 3}0.422{col 66}{space 4}-2.472954{col 79}{space 3} 5.911019
{txt}{space 19}1975  {c |}{col 26}{res}{space 2}  1.72293{col 38}{space 2} 2.330133{col 49}{space 1}    0.74{col 58}{space 3}0.460{col 66}{space 4}-2.844046{col 79}{space 3} 6.289906
{txt}{space 19}1976  {c |}{col 26}{res}{space 2} 2.378858{col 38}{space 2} 2.386248{col 49}{space 1}    1.00{col 58}{space 3}0.319{col 66}{space 4}-2.298102{col 79}{space 3} 7.055819
{txt}{space 19}1977  {c |}{col 26}{res}{space 2} 2.526453{col 38}{space 2} 2.548718{col 49}{space 1}    0.99{col 58}{space 3}0.322{col 66}{space 4}-2.468942{col 79}{space 3} 7.521848
{txt}{space 19}1978  {c |}{col 26}{res}{space 2} 2.637209{col 38}{space 2}  2.70638{col 49}{space 1}    0.97{col 58}{space 3}0.330{col 66}{space 4}-2.667198{col 79}{space 3} 7.941616
{txt}{space 19}1979  {c |}{col 26}{res}{space 2} 2.486307{col 38}{space 2} 2.836824{col 49}{space 1}    0.88{col 58}{space 3}0.381{col 66}{space 4}-3.073767{col 79}{space 3} 8.046381
{txt}{space 19}1980  {c |}{col 26}{res}{space 2} 2.512488{col 38}{space 2} 2.786995{col 49}{space 1}    0.90{col 58}{space 3}0.367{col 66}{space 4}-2.949921{col 79}{space 3} 7.974897
{txt}{space 19}1981  {c |}{col 26}{res}{space 2} 2.753206{col 38}{space 2} 2.754929{col 49}{space 1}    1.00{col 58}{space 3}0.318{col 66}{space 4}-2.646355{col 79}{space 3} 8.152768
{txt}{space 19}1982  {c |}{col 26}{res}{space 2} 2.021711{col 38}{space 2} 2.722967{col 49}{space 1}    0.74{col 58}{space 3}0.458{col 66}{space 4}-3.315206{col 79}{space 3} 7.358629
{txt}{space 19}1983  {c |}{col 26}{res}{space 2} 1.977702{col 38}{space 2} 2.702202{col 49}{space 1}    0.73{col 58}{space 3}0.464{col 66}{space 4}-3.318515{col 79}{space 3}  7.27392
{txt}{space 24} {c |}
{space 19}state {c |}
{space 21}AR  {c |}{col 26}{res}{space 2}-15.48811{col 38}{space 2} 2.801115{col 49}{space 1}   -5.53{col 58}{space 3}0.000{col 66}{space 4}-20.97819{col 79}{space 3}-9.998022
{txt}{space 21}AZ  {c |}{col 26}{res}{space 2}-29.91044{col 38}{space 2}  7.18073{col 49}{space 1}   -4.17{col 58}{space 3}0.000{col 66}{space 4}-43.98441{col 79}{space 3}-15.83646
{txt}{space 21}CA  {c |}{col 26}{res}{space 2}-31.62477{col 38}{space 2} 9.267552{col 49}{space 1}   -3.41{col 58}{space 3}0.001{col 66}{space 4}-49.78884{col 79}{space 3} -13.4607
{txt}{space 21}CO  {c |}{col 26}{res}{space 2}-32.37027{col 38}{space 2}  5.97118{col 49}{space 1}   -5.42{col 58}{space 3}0.000{col 66}{space 4}-44.07357{col 79}{space 3}-20.66698
{txt}{space 21}CT  {c |}{col 26}{res}{space 2}-31.86633{col 38}{space 2}   5.6157{col 49}{space 1}   -5.67{col 58}{space 3}0.000{col 66}{space 4} -42.8729{col 79}{space 3}-20.85976
{txt}{space 21}DE  {c |}{col 26}{res}{space 2}-32.03447{col 38}{space 2} 6.720771{col 49}{space 1}   -4.77{col 58}{space 3}0.000{col 66}{space 4}-45.20694{col 79}{space 3}  -18.862
{txt}{space 21}FL  {c |}{col 26}{res}{space 2}-26.35724{col 38}{space 2} 6.290106{col 49}{space 1}   -4.19{col 58}{space 3}0.000{col 66}{space 4}-38.68562{col 79}{space 3}-14.02886
{txt}{space 21}GA  {c |}{col 26}{res}{space 2}-17.82776{col 38}{space 2} 1.888057{col 49}{space 1}   -9.44{col 58}{space 3}0.000{col 66}{space 4}-21.52828{col 79}{space 3}-14.12723
{txt}{space 21}IA  {c |}{col 26}{res}{space 2}-18.12398{col 38}{space 2} 2.051982{col 49}{space 1}   -8.83{col 58}{space 3}0.000{col 66}{space 4}-22.14579{col 79}{space 3}-14.10217
{txt}{space 21}ID  {c |}{col 26}{res}{space 2}-20.20774{col 38}{space 2} 5.253279{col 49}{space 1}   -3.85{col 58}{space 3}0.000{col 66}{space 4}-30.50398{col 79}{space 3}-9.911507
{txt}{space 21}IL  {c |}{col 26}{res}{space 2}-31.71803{col 38}{space 2} 6.702076{col 49}{space 1}   -4.73{col 58}{space 3}0.000{col 66}{space 4}-44.85386{col 79}{space 3} -18.5822
{txt}{space 21}IN  {c |}{col 26}{res}{space 2}-22.50768{col 38}{space 2}   2.1755{col 49}{space 1}  -10.35{col 58}{space 3}0.000{col 66}{space 4}-26.77158{col 79}{space 3}-18.24377
{txt}{space 21}KS  {c |}{col 26}{res}{space 2}-6.281682{col 38}{space 2} 3.001116{col 49}{space 1}   -2.09{col 58}{space 3}0.036{col 66}{space 4}-12.16376{col 79}{space 3}-.3996036
{txt}{space 21}KY  {c |}{col 26}{res}{space 2} -18.3099{col 38}{space 2} 2.855506{col 49}{space 1}   -6.41{col 58}{space 3}0.000{col 66}{space 4}-23.90659{col 79}{space 3}-12.71321
{txt}{space 21}LA  {c |}{col 26}{res}{space 2}-3.002364{col 38}{space 2} 2.821137{col 49}{space 1}   -1.06{col 58}{space 3}0.287{col 66}{space 4} -8.53169{col 79}{space 3} 2.526962
{txt}{space 21}MA  {c |}{col 26}{res}{space 2}-15.08287{col 38}{space 2} 6.974662{col 49}{space 1}   -2.16{col 58}{space 3}0.031{col 66}{space 4}-28.75295{col 79}{space 3} -1.41278
{txt}{space 21}MD  {c |}{col 26}{res}{space 2}-31.23335{col 38}{space 2} 5.219355{col 49}{space 1}   -5.98{col 58}{space 3}0.000{col 66}{space 4} -41.4631{col 79}{space 3} -21.0036
{txt}{space 21}ME  {c |}{col 26}{res}{space 2}-20.04467{col 38}{space 2} 4.649937{col 49}{space 1}   -4.31{col 58}{space 3}0.000{col 66}{space 4}-29.15838{col 79}{space 3}-10.93096
{txt}{space 21}MI  {c |}{col 26}{res}{space 2}-7.847191{col 38}{space 2} 4.502606{col 49}{space 1}   -1.74{col 58}{space 3}0.081{col 66}{space 4}-16.67214{col 79}{space 3} .9777553
{txt}{space 21}MN  {c |}{col 26}{res}{space 2}-24.92395{col 38}{space 2} 2.653227{col 49}{space 1}   -9.39{col 58}{space 3}0.000{col 66}{space 4}-30.12418{col 79}{space 3}-19.72372
{txt}{space 21}MO  {c |}{col 26}{res}{space 2}-24.16364{col 38}{space 2} 2.996309{col 49}{space 1}   -8.06{col 58}{space 3}0.000{col 66}{space 4}-30.03629{col 79}{space 3}-18.29098
{txt}{space 21}MS  {c |}{col 26}{res}{space 2} -17.5764{col 38}{space 2} 3.673053{col 49}{space 1}   -4.79{col 58}{space 3}0.000{col 66}{space 4}-24.77545{col 79}{space 3}-10.37734
{txt}{space 21}MT  {c |}{col 26}{res}{space 2}-25.06658{col 38}{space 2} 5.016336{col 49}{space 1}   -5.00{col 58}{space 3}0.000{col 66}{space 4}-34.89842{col 79}{space 3}-15.23474
{txt}{space 21}NC  {c |}{col 26}{res}{space 2} 7.700049{col 38}{space 2} 5.105287{col 49}{space 1}    1.51{col 58}{space 3}0.131{col 66}{space 4}-2.306129{col 79}{space 3} 17.70623
{txt}{space 21}ND  {c |}{col 26}{res}{space 2}-22.48736{col 38}{space 2} 6.332078{col 49}{space 1}   -3.55{col 58}{space 3}0.000{col 66}{space 4}  -34.898{col 79}{space 3}-10.07671
{txt}{space 21}NH  {c |}{col 26}{res}{space 2}-18.84076{col 38}{space 2} 5.707228{col 49}{space 1}   -3.30{col 58}{space 3}0.001{col 66}{space 4}-30.02672{col 79}{space 3}-7.654802
{txt}{space 21}NJ  {c |}{col 26}{res}{space 2}-36.06701{col 38}{space 2} 7.997545{col 49}{space 1}   -4.51{col 58}{space 3}0.000{col 66}{space 4}-51.74191{col 79}{space 3}-20.39211
{txt}{space 21}NM  {c |}{col 26}{res}{space 2}-25.91892{col 38}{space 2} 4.932179{col 49}{space 1}   -5.26{col 58}{space 3}0.000{col 66}{space 4}-35.58582{col 79}{space 3}-16.25203
{txt}{space 21}NV  {c |}{col 26}{res}{space 2}-15.15411{col 38}{space 2} 10.25562{col 49}{space 1}   -1.48{col 58}{space 3}0.140{col 66}{space 4}-35.25476{col 79}{space 3} 4.946538
{txt}{space 21}NY  {c |}{col 26}{res}{space 2}-31.93534{col 38}{space 2} 8.215507{col 49}{space 1}   -3.89{col 58}{space 3}0.000{col 66}{space 4}-48.03743{col 79}{space 3}-15.83324
{txt}{space 21}OH  {c |}{col 26}{res}{space 2}-26.13212{col 38}{space 2} 4.744621{col 49}{space 1}   -5.51{col 58}{space 3}0.000{col 66}{space 4} -35.4314{col 79}{space 3}-16.83283
{txt}{space 21}OK  {c |}{col 26}{res}{space 2} -4.95551{col 38}{space 2} 2.778109{col 49}{space 1}   -1.78{col 58}{space 3}0.074{col 66}{space 4} -10.4005{col 79}{space 3}  .489483
{txt}{space 21}OR  {c |}{col 26}{res}{space 2}-27.05712{col 38}{space 2} 3.208379{col 49}{space 1}   -8.43{col 58}{space 3}0.000{col 66}{space 4}-33.34543{col 79}{space 3}-20.76881
{txt}{space 21}PA  {c |}{col 26}{res}{space 2}-24.06377{col 38}{space 2} 5.151244{col 49}{space 1}   -4.67{col 58}{space 3}0.000{col 66}{space 4}-34.16003{col 79}{space 3}-13.96752
{txt}{space 21}RI  {c |}{col 26}{res}{space 2} -37.1285{col 38}{space 2} 9.776804{col 49}{space 1}   -3.80{col 58}{space 3}0.000{col 66}{space 4}-56.29069{col 79}{space 3}-17.96632
{txt}{space 21}SC  {c |}{col 26}{res}{space 2}-13.35638{col 38}{space 2} 2.742522{col 49}{space 1}   -4.87{col 58}{space 3}0.000{col 66}{space 4}-18.73162{col 79}{space 3}-7.981131
{txt}{space 21}SD  {c |}{col 26}{res}{space 2}-22.44873{col 38}{space 2} 6.261312{col 49}{space 1}   -3.59{col 58}{space 3}0.000{col 66}{space 4}-34.72068{col 79}{space 3}-10.17678
{txt}{space 21}TN  {c |}{col 26}{res}{space 2}-21.22732{col 38}{space 2} 1.641028{col 49}{space 1}  -12.94{col 58}{space 3}0.000{col 66}{space 4}-24.44368{col 79}{space 3}-18.01097
{txt}{space 21}TX  {c |}{col 26}{res}{space 2}-54.07281{col 38}{space 2} 6.415076{col 49}{space 1}   -8.43{col 58}{space 3}0.000{col 66}{space 4}-66.64613{col 79}{space 3} -41.4995
{txt}{space 21}UT  {c |}{col 26}{res}{space 2}-28.88826{col 38}{space 2} 7.815553{col 49}{space 1}   -3.70{col 58}{space 3}0.000{col 66}{space 4}-44.20647{col 79}{space 3}-13.57006
{txt}{space 21}VA  {c |}{col 26}{res}{space 2}-20.54229{col 38}{space 2} 2.636256{col 49}{space 1}   -7.79{col 58}{space 3}0.000{col 66}{space 4}-25.70926{col 79}{space 3}-15.37532
{txt}{space 21}VT  {c |}{col 26}{res}{space 2}-15.18401{col 38}{space 2} 8.519786{col 49}{space 1}   -1.78{col 58}{space 3}0.075{col 66}{space 4}-31.88248{col 79}{space 3} 1.514461
{txt}{space 21}WA  {c |}{col 26}{res}{space 2}-29.84689{col 38}{space 2} 4.032438{col 49}{space 1}   -7.40{col 58}{space 3}0.000{col 66}{space 4}-37.75032{col 79}{space 3}-21.94346
{txt}{space 21}WI  {c |}{col 26}{res}{space 2}-21.46935{col 38}{space 2} 2.364732{col 49}{space 1}   -9.08{col 58}{space 3}0.000{col 66}{space 4}-26.10414{col 79}{space 3}-16.83456
{txt}{space 21}WV  {c |}{col 26}{res}{space 2}-41.25792{col 38}{space 2} 6.093406{col 49}{space 1}   -6.77{col 58}{space 3}0.000{col 66}{space 4}-53.20078{col 79}{space 3}-29.31507
{txt}{space 21}WY  {c |}{col 26}{res}{space 2}-27.46887{col 38}{space 2} 7.620275{col 49}{space 1}   -3.60{col 58}{space 3}0.000{col 66}{space 4}-42.40434{col 79}{space 3}-12.53341
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 19}/cut1 {c |}{col 26}{res}{space 2}-23.43078{col 38}{space 2} 40.75204{col 66}{space 4}-103.3033{col 79}{space 3} 56.44176
{txt}{space 19}/cut2 {c |}{col 26}{res}{space 2}-18.67071{col 38}{space 2} 40.78086{col 66}{space 4}-98.59972{col 79}{space 3}  61.2583
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: 188 observations completely determined.{txt}  Standard errors questionable.{p_end}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_atrue_divided_gov_e.tex"'"':Table_atrue_divided_gov_e.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_e.txt", label"':seeout}
{p 0 6 2}note: 50.state#c.year omitted because of collinearity{p_end}
{res}
{txt}Linear regression, absorbing indicators{col 49}Number of obs{col 67}= {res}       893
{txt}Absorbed variable: {bf:state}{col 49}No. of categories{col 67}= {res}        47
{txt}{col 49}{help j_robustsingular##|_new:F(  22,     46)}{col 67}=          {res}.
{txt}{col 49}Prob > F{col 67}=          {res}.
{txt}{col 49}R-squared{col 67}= {res}    0.8485
{txt}{col 49}Adj R-squared{col 67}= {res}    0.8261
{txt}{col 49}Root MSE{col 67}= {res}    0.1249

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~m{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_e {c |}{col 20}{res}{space 2} .0333586{col 32}{space 2} .0166405{col 43}{space 1}    2.00{col 52}{space 3}0.051{col 60}{space 4} -.000137{col 73}{space 3} .0668542
{txt}{space 10}ideociti {c |}{col 20}{res}{space 2} .0181878{col 32}{space 2} .1396851{col 43}{space 1}    0.13{col 52}{space 3}0.897{col 60}{space 4}-.2629836{col 73}{space 3} .2993593
{txt}{space 13}urban {c |}{col 20}{res}{space 2} 3.040515{col 32}{space 2} 3.690208{col 43}{space 1}    0.82{col 52}{space 3}0.414{col 60}{space 4}-4.387489{col 73}{space 3} 10.46852
{txt}{space 12}income {c |}{col 20}{res}{space 2} .0244673{col 32}{space 2} .0432359{col 43}{space 1}    0.57{col 52}{space 3}0.574{col 60}{space 4}-.0625621{col 73}{space 3} .1114967
{txt}{space 10}lfullemp {c |}{col 20}{res}{space 2}-.0086445{col 32}{space 2}  .137089{col 43}{space 1}   -0.06{col 52}{space 3}0.950{col 60}{space 4}-.2845904{col 73}{space 3} .2673015
{txt}{space 18} {c |}
{space 14}year {c |}
{space 13}1966  {c |}{col 20}{res}{space 2} .0047279{col 32}{space 2} .0380908{col 43}{space 1}    0.12{col 52}{space 3}0.902{col 60}{space 4}-.0719449{col 73}{space 3} .0814007
{txt}{space 13}1967  {c |}{col 20}{res}{space 2} .0090135{col 32}{space 2} .0499646{col 43}{space 1}    0.18{col 52}{space 3}0.858{col 60}{space 4}-.0915601{col 73}{space 3} .1095871
{txt}{space 13}1968  {c |}{col 20}{res}{space 2} -.009757{col 32}{space 2} .0784622{col 43}{space 1}   -0.12{col 52}{space 3}0.902{col 60}{space 4}-.1676932{col 73}{space 3} .1481793
{txt}{space 13}1969  {c |}{col 20}{res}{space 2}-.0028686{col 32}{space 2}  .095784{col 43}{space 1}   -0.03{col 52}{space 3}0.976{col 60}{space 4}-.1956717{col 73}{space 3} .1899345
{txt}{space 13}1970  {c |}{col 20}{res}{space 2}-.0363825{col 32}{space 2} .1124912{col 43}{space 1}   -0.32{col 52}{space 3}0.748{col 60}{space 4}-.2628156{col 73}{space 3} .1900506
{txt}{space 13}1971  {c |}{col 20}{res}{space 2}-.0675714{col 32}{space 2} .1260755{col 43}{space 1}   -0.54{col 52}{space 3}0.595{col 60}{space 4}-.3213481{col 73}{space 3} .1862054
{txt}{space 13}1972  {c |}{col 20}{res}{space 2}-.1035974{col 32}{space 2}  .149064{col 43}{space 1}   -0.69{col 52}{space 3}0.491{col 60}{space 4}-.4036476{col 73}{space 3} .1964529
{txt}{space 13}1973  {c |}{col 20}{res}{space 2}-.1196761{col 32}{space 2} .1672791{col 43}{space 1}   -0.72{col 52}{space 3}0.478{col 60}{space 4}-.4563914{col 73}{space 3} .2170392
{txt}{space 13}1974  {c |}{col 20}{res}{space 2}-.1354139{col 32}{space 2} .1671023{col 43}{space 1}   -0.81{col 52}{space 3}0.422{col 60}{space 4}-.4717735{col 73}{space 3} .2009457
{txt}{space 13}1975  {c |}{col 20}{res}{space 2}-.1342491{col 32}{space 2} .1861481{col 43}{space 1}   -0.72{col 52}{space 3}0.474{col 60}{space 4}-.5089458{col 73}{space 3} .2404477
{txt}{space 13}1976  {c |}{col 20}{res}{space 2}-.1207195{col 32}{space 2} .2067366{col 43}{space 1}   -0.58{col 52}{space 3}0.562{col 60}{space 4}-.5368588{col 73}{space 3} .2954197
{txt}{space 13}1977  {c |}{col 20}{res}{space 2}-.1507941{col 32}{space 2} .2237654{col 43}{space 1}   -0.67{col 52}{space 3}0.504{col 60}{space 4}-.6012104{col 73}{space 3} .2996222
{txt}{space 13}1978  {c |}{col 20}{res}{space 2} -.184259{col 32}{space 2} .2447714{col 43}{space 1}   -0.75{col 52}{space 3}0.455{col 60}{space 4}-.6769583{col 73}{space 3} .3084403
{txt}{space 13}1979  {c |}{col 20}{res}{space 2} -.207137{col 32}{space 2} .2520003{col 43}{space 1}   -0.82{col 52}{space 3}0.415{col 60}{space 4}-.7143872{col 73}{space 3} .3001132
{txt}{space 13}1980  {c |}{col 20}{res}{space 2}-.2200036{col 32}{space 2} .2481723{col 43}{space 1}   -0.89{col 52}{space 3}0.380{col 60}{space 4}-.7195484{col 73}{space 3} .2795413
{txt}{space 13}1981  {c |}{col 20}{res}{space 2}-.2440594{col 32}{space 2} .2605373{col 43}{space 1}   -0.94{col 52}{space 3}0.354{col 60}{space 4}-.7684937{col 73}{space 3} .2803749
{txt}{space 13}1982  {c |}{col 20}{res}{space 2}-.2689428{col 32}{space 2} .2718986{col 43}{space 1}   -0.99{col 52}{space 3}0.328{col 60}{space 4}-.8162463{col 73}{space 3} .2783607
{txt}{space 13}1983  {c |}{col 20}{res}{space 2}-.2967786{col 32}{space 2} .2888665{col 43}{space 1}   -1.03{col 52}{space 3}0.310{col 60}{space 4}-.8782366{col 73}{space 3} .2846795
{txt}{space 18} {c |}
{space 6}state#c.year {c |}
{space 15}AL  {c |}{col 20}{res}{space 2} .0068617{col 32}{space 2} .0058996{col 43}{space 1}    1.16{col 52}{space 3}0.251{col 60}{space 4}-.0050136{col 73}{space 3}  .018737
{txt}{space 15}AR  {c |}{col 20}{res}{space 2}  .056417{col 32}{space 2} .0048103{col 43}{space 1}   11.73{col 52}{space 3}0.000{col 60}{space 4} .0467343{col 73}{space 3} .0660997
{txt}{space 15}AZ  {c |}{col 20}{res}{space 2} .0382675{col 32}{space 2} .0099127{col 43}{space 1}    3.86{col 52}{space 3}0.000{col 60}{space 4} .0183142{col 73}{space 3} .0582208
{txt}{space 15}CA  {c |}{col 20}{res}{space 2} .0082045{col 32}{space 2} .0065003{col 43}{space 1}    1.26{col 52}{space 3}0.213{col 60}{space 4}-.0048799{col 73}{space 3} .0212889
{txt}{space 15}CO  {c |}{col 20}{res}{space 2} .0009951{col 32}{space 2}  .002444{col 43}{space 1}    0.41{col 52}{space 3}0.686{col 60}{space 4}-.0039244{col 73}{space 3} .0059145
{txt}{space 15}CT  {c |}{col 20}{res}{space 2} .0116547{col 32}{space 2} .0086677{col 43}{space 1}    1.34{col 52}{space 3}0.185{col 60}{space 4}-.0057924{col 73}{space 3} .0291018
{txt}{space 15}DE  {c |}{col 20}{res}{space 2} .0281798{col 32}{space 2} .0118701{col 43}{space 1}    2.37{col 52}{space 3}0.022{col 60}{space 4} .0042865{col 73}{space 3}  .052073
{txt}{space 15}FL  {c |}{col 20}{res}{space 2} .0322541{col 32}{space 2}  .005221{col 43}{space 1}    6.18{col 52}{space 3}0.000{col 60}{space 4} .0217448{col 73}{space 3} .0427635
{txt}{space 15}GA  {c |}{col 20}{res}{space 2} .0050741{col 32}{space 2} .0064416{col 43}{space 1}    0.79{col 52}{space 3}0.435{col 60}{space 4}-.0078922{col 73}{space 3} .0180404
{txt}{space 15}IA  {c |}{col 20}{res}{space 2} .0221546{col 32}{space 2} .0059289{col 43}{space 1}    3.74{col 52}{space 3}0.001{col 60}{space 4} .0102204{col 73}{space 3} .0340887
{txt}{space 15}ID  {c |}{col 20}{res}{space 2} .0365658{col 32}{space 2} .0092069{col 43}{space 1}    3.97{col 52}{space 3}0.000{col 60}{space 4} .0180333{col 73}{space 3} .0550984
{txt}{space 15}IL  {c |}{col 20}{res}{space 2} .0108299{col 32}{space 2} .0092802{col 43}{space 1}    1.17{col 52}{space 3}0.249{col 60}{space 4}-.0078503{col 73}{space 3}   .02951
{txt}{space 15}IN  {c |}{col 20}{res}{space 2} .0138032{col 32}{space 2} .0116828{col 43}{space 1}    1.18{col 52}{space 3}0.243{col 60}{space 4} -.009713{col 73}{space 3} .0373194
{txt}{space 15}KS  {c |}{col 20}{res}{space 2} .0046891{col 32}{space 2} .0045435{col 43}{space 1}    1.03{col 52}{space 3}0.307{col 60}{space 4}-.0044566{col 73}{space 3} .0138348
{txt}{space 15}KY  {c |}{col 20}{res}{space 2} .0108679{col 32}{space 2} .0092069{col 43}{space 1}    1.18{col 52}{space 3}0.244{col 60}{space 4}-.0076647{col 73}{space 3} .0294005
{txt}{space 15}LA  {c |}{col 20}{res}{space 2} .0048115{col 32}{space 2} .0035259{col 43}{space 1}    1.36{col 52}{space 3}0.179{col 60}{space 4}-.0022858{col 73}{space 3} .0119088
{txt}{space 15}MA  {c |}{col 20}{res}{space 2}  .014489{col 32}{space 2} .0118131{col 43}{space 1}    1.23{col 52}{space 3}0.226{col 60}{space 4}-.0092896{col 73}{space 3} .0382676
{txt}{space 15}MD  {c |}{col 20}{res}{space 2} .0008994{col 32}{space 2} .0059584{col 43}{space 1}    0.15{col 52}{space 3}0.881{col 60}{space 4}-.0110943{col 73}{space 3} .0128931
{txt}{space 15}ME  {c |}{col 20}{res}{space 2} .0221761{col 32}{space 2} .0208023{col 43}{space 1}    1.07{col 52}{space 3}0.292{col 60}{space 4}-.0196969{col 73}{space 3}  .064049
{txt}{space 15}MI  {c |}{col 20}{res}{space 2} .0206199{col 32}{space 2} .0192461{col 43}{space 1}    1.07{col 52}{space 3}0.290{col 60}{space 4}-.0181204{col 73}{space 3} .0593603
{txt}{space 15}MN  {c |}{col 20}{res}{space 2} .0075077{col 32}{space 2} .0058938{col 43}{space 1}    1.27{col 52}{space 3}0.209{col 60}{space 4}-.0043559{col 73}{space 3} .0193712
{txt}{space 15}MO  {c |}{col 20}{res}{space 2} .0147987{col 32}{space 2} .0132727{col 43}{space 1}    1.11{col 52}{space 3}0.271{col 60}{space 4}-.0119179{col 73}{space 3} .0415154
{txt}{space 15}MS  {c |}{col 20}{res}{space 2} .0795182{col 32}{space 2} .0061678{col 43}{space 1}   12.89{col 52}{space 3}0.000{col 60}{space 4}  .067103{col 73}{space 3} .0919335
{txt}{space 15}MT  {c |}{col 20}{res}{space 2} .0890082{col 32}{space 2} .0097005{col 43}{space 1}    9.18{col 52}{space 3}0.000{col 60}{space 4} .0694821{col 73}{space 3} .1085344
{txt}{space 15}NC  {c |}{col 20}{res}{space 2} .0028095{col 32}{space 2} .0061622{col 43}{space 1}    0.46{col 52}{space 3}0.651{col 60}{space 4}-.0095944{col 73}{space 3} .0152134
{txt}{space 15}ND  {c |}{col 20}{res}{space 2} .0743731{col 32}{space 2} .0115663{col 43}{space 1}    6.43{col 52}{space 3}0.000{col 60}{space 4} .0510912{col 73}{space 3} .0976549
{txt}{space 15}NH  {c |}{col 20}{res}{space 2} .0226546{col 32}{space 2} .0229455{col 43}{space 1}    0.99{col 52}{space 3}0.329{col 60}{space 4}-.0235322{col 73}{space 3} .0688415
{txt}{space 15}NJ  {c |}{col 20}{res}{space 2}   .01116{col 32}{space 2} .0101671{col 43}{space 1}    1.10{col 52}{space 3}0.278{col 60}{space 4}-.0093053{col 73}{space 3} .0316254
{txt}{space 15}NM  {c |}{col 20}{res}{space 2} .0063417{col 32}{space 2} .0071669{col 43}{space 1}    0.88{col 52}{space 3}0.381{col 60}{space 4}-.0080845{col 73}{space 3}  .020768
{txt}{space 15}NV  {c |}{col 20}{res}{space 2}-.0036994{col 32}{space 2} .0129956{col 43}{space 1}   -0.28{col 52}{space 3}0.777{col 60}{space 4}-.0298582{col 73}{space 3} .0224594
{txt}{space 15}NY  {c |}{col 20}{res}{space 2} .0155704{col 32}{space 2} .0147824{col 43}{space 1}    1.05{col 52}{space 3}0.298{col 60}{space 4}-.0141849{col 73}{space 3} .0453258
{txt}{space 15}OH  {c |}{col 20}{res}{space 2} .0149572{col 32}{space 2} .0144999{col 43}{space 1}    1.03{col 52}{space 3}0.308{col 60}{space 4}-.0142295{col 73}{space 3}  .044144
{txt}{space 15}OK  {c |}{col 20}{res}{space 2} .0093924{col 32}{space 2} .0082386{col 43}{space 1}    1.14{col 52}{space 3}0.260{col 60}{space 4}-.0071909{col 73}{space 3} .0259758
{txt}{space 15}OR  {c |}{col 20}{res}{space 2} .0076874{col 32}{space 2} .0057643{col 43}{space 1}    1.33{col 52}{space 3}0.189{col 60}{space 4}-.0039156{col 73}{space 3} .0192903
{txt}{space 15}PA  {c |}{col 20}{res}{space 2} .0178508{col 32}{space 2} .0162663{col 43}{space 1}    1.10{col 52}{space 3}0.278{col 60}{space 4}-.0148916{col 73}{space 3} .0505932
{txt}{space 15}RI  {c |}{col 20}{res}{space 2} .0142811{col 32}{space 2} .0122673{col 43}{space 1}    1.16{col 52}{space 3}0.250{col 60}{space 4}-.0104117{col 73}{space 3}  .038974
{txt}{space 15}SC  {c |}{col 20}{res}{space 2} .0482721{col 32}{space 2} .0135107{col 43}{space 1}    3.57{col 52}{space 3}0.001{col 60}{space 4} .0210765{col 73}{space 3} .0754677
{txt}{space 15}SD  {c |}{col 20}{res}{space 2} .0814425{col 32}{space 2} .0054836{col 43}{space 1}   14.85{col 52}{space 3}0.000{col 60}{space 4} .0704047{col 73}{space 3} .0924804
{txt}{space 15}TN  {c |}{col 20}{res}{space 2} .0058636{col 32}{space 2} .0052468{col 43}{space 1}    1.12{col 52}{space 3}0.270{col 60}{space 4}-.0046977{col 73}{space 3} .0164249
{txt}{space 15}TX  {c |}{col 20}{res}{space 2} .0078599{col 32}{space 2} .0067948{col 43}{space 1}    1.16{col 52}{space 3}0.253{col 60}{space 4}-.0058172{col 73}{space 3} .0215371
{txt}{space 15}UT  {c |}{col 20}{res}{space 2}  .000352{col 32}{space 2} .0104278{col 43}{space 1}    0.03{col 52}{space 3}0.973{col 60}{space 4}-.0206381{col 73}{space 3} .0213421
{txt}{space 15}VA  {c |}{col 20}{res}{space 2}-.0008525{col 32}{space 2} .0057055{col 43}{space 1}   -0.15{col 52}{space 3}0.882{col 60}{space 4} -.012337{col 73}{space 3} .0106321
{txt}{space 15}VT  {c |}{col 20}{res}{space 2}  .015256{col 32}{space 2} .0125301{col 43}{space 1}    1.22{col 52}{space 3}0.230{col 60}{space 4}-.0099658{col 73}{space 3} .0404777
{txt}{space 15}WA  {c |}{col 20}{res}{space 2}  .009496{col 32}{space 2} .0068253{col 43}{space 1}    1.39{col 52}{space 3}0.171{col 60}{space 4}-.0042426{col 73}{space 3} .0232346
{txt}{space 15}WI  {c |}{col 20}{res}{space 2} .0144687{col 32}{space 2} .0130014{col 43}{space 1}    1.11{col 52}{space 3}0.272{col 60}{space 4}-.0117017{col 73}{space 3} .0406392
{txt}{space 15}WV  {c |}{col 20}{res}{space 2} .0186858{col 32}{space 2} .0173773{col 43}{space 1}    1.08{col 52}{space 3}0.288{col 60}{space 4}-.0162928{col 73}{space 3} .0536645
{txt}{space 15}WY  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}-40.44804{col 32}{space 2} 14.91773{col 43}{space 1}   -2.71{col 52}{space 3}0.009{col 60}{space 4}-70.47589{col 73}{space 3} -10.4202
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_atrue_divided_gov_e.tex"'"':Table_atrue_divided_gov_e.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_atrue_divided_gov_e.txt", label"':seeout}

{com}. 
. 
. *\Table a5
. 
. 
. * table 1 column 2
. reghdfe civil_service_reform_ipe sen_gov_share hs_gov_share dem_gov_share divided_either , a(state year )    cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   4{txt},{res}     46{txt}){col 67}= {res}      2.86
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0336
{txt}{col 51}R-squared{col 67}= {res}    0.6339
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6006
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0202
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4273

{txt}{ralign 80:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}civil_servic~e{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}sen_gov_share {c |}{col 16}{res}{space 2} .0040375{col 28}{space 2} .0036616{col 39}{space 1}    1.10{col 48}{space 3}0.276{col 56}{space 4}-.0033329{col 69}{space 3} .0114078
{txt}{space 2}hs_gov_share {c |}{col 16}{res}{space 2}-.0021386{col 28}{space 2} .0034529{col 39}{space 1}   -0.62{col 48}{space 3}0.539{col 56}{space 4} -.009089{col 69}{space 3} .0048117
{txt}{space 1}dem_gov_share {c |}{col 16}{res}{space 2}-.0005162{col 28}{space 2} .0013396{col 39}{space 1}   -0.39{col 48}{space 3}0.702{col 56}{space 4}-.0032127{col 69}{space 3} .0021802
{txt}divided_either {c |}{col 16}{res}{space 2} .1749653{col 28}{space 2} .0635026{col 39}{space 1}    2.76{col 48}{space 3}0.008{col 56}{space 4} .0471412{col 69}{space 3} .3027895
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 1.163576{col 28}{space 2} .1207516{col 39}{space 1}    9.64{col 48}{space 3}0.000{col 56}{space 4} .9205161{col 69}{space 3} 1.406637
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table_a5, tex replace keep(divided_either)  label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X, Shares, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{txt}{stata `"shellout using `"Table_a5.tex"'"':Table_a5.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_a5.txt", label"':seeout}

{com}. * table 1 column 3
. reghdfe civil_service_reform_ipe true_divided_gov_a sen_gov_share hs_gov_share dem_gov_share  , a(state year)   cl(state) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   4{txt},{res}     46{txt}){col 67}= {res}      2.86
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0336
{txt}{col 51}R-squared{col 67}= {res}    0.6344
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6012
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0215
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4270

{txt}{ralign 84:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 20}{c |}{col 32}    Robust
{col 1}civil_service_re~e{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
true_divided_gov_a {c |}{col 20}{res}{space 2} .1482992{col 32}{space 2}  .051893{col 43}{space 1}    2.86{col 52}{space 3}0.006{col 60}{space 4} .0438439{col 73}{space 3} .2527544
{txt}{space 5}sen_gov_share {c |}{col 20}{res}{space 2} .0029454{col 32}{space 2} .0036006{col 43}{space 1}    0.82{col 52}{space 3}0.418{col 60}{space 4}-.0043023{col 73}{space 3} .0101931
{txt}{space 6}hs_gov_share {c |}{col 20}{res}{space 2}-.0031721{col 32}{space 2} .0034041{col 43}{space 1}   -0.93{col 52}{space 3}0.356{col 60}{space 4}-.0100242{col 73}{space 3} .0036801
{txt}{space 5}dem_gov_share {c |}{col 20}{res}{space 2}-.0006222{col 32}{space 2} .0013264{col 43}{space 1}   -0.47{col 52}{space 3}0.641{col 60}{space 4}-.0032922{col 73}{space 3} .0020477
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 1.318492{col 32}{space 2} .0745637{col 43}{space 1}   17.68{col 52}{space 3}0.000{col 60}{space 4} 1.168403{col 73}{space 3}  1.46858
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table_a5, tex append keep(true_divided_gov_a) label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X, Shares, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_a5.tex"'"':Table_a5.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_a5.txt", label"':seeout}

{com}. * table 1 column 5
. reghdfe civil_service_reform_ipe divided_either ideociti urban income  lfullemp sen_gov_share hs_gov_share dem_gov_share, a(state##c.year year)   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 6 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   8{txt},{res}     46{txt}){col 67}= {res}      1.60
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.1521
{txt}{col 51}R-squared{col 67}= {res}    0.8385
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8112
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0250
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.2938

{txt}{ralign 80:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}civil_servic~e{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_either {c |}{col 16}{res}{space 2} .0766915{col 28}{space 2} .0520539{col 39}{space 1}    1.47{col 48}{space 3}0.147{col 56}{space 4}-.0280874{col 69}{space 3} .1814705
{txt}{space 6}ideociti {c |}{col 16}{res}{space 2} .6164137{col 28}{space 2} .2478529{col 39}{space 1}    2.49{col 48}{space 3}0.017{col 56}{space 4} .1175116{col 69}{space 3} 1.115316
{txt}{space 9}urban {c |}{col 16}{res}{space 2} 3.659696{col 28}{space 2} 7.757516{col 39}{space 1}    0.47{col 48}{space 3}0.639{col 56}{space 4}-11.95537{col 69}{space 3} 19.27477
{txt}{space 8}income {c |}{col 16}{res}{space 2} .0431547{col 28}{space 2} .0829049{col 39}{space 1}    0.52{col 48}{space 3}0.605{col 56}{space 4}-.1237243{col 69}{space 3} .2100337
{txt}{space 6}lfullemp {c |}{col 16}{res}{space 2} .2426215{col 28}{space 2} .3728879{col 39}{space 1}    0.65{col 48}{space 3}0.519{col 56}{space 4}-.5079629{col 69}{space 3}  .993206
{txt}{space 1}sen_gov_share {c |}{col 16}{res}{space 2} .0009622{col 28}{space 2} .0028832{col 39}{space 1}    0.33{col 48}{space 3}0.740{col 56}{space 4}-.0048414{col 69}{space 3} .0067657
{txt}{space 2}hs_gov_share {c |}{col 16}{res}{space 2}-.0002056{col 28}{space 2}   .00305{col 39}{space 1}   -0.07{col 48}{space 3}0.947{col 56}{space 4}-.0063449{col 69}{space 3} .0059337
{txt}{space 1}dem_gov_share {c |}{col 16}{res}{space 2}-.0001554{col 28}{space 2} .0010285{col 39}{space 1}   -0.15{col 48}{space 3}0.881{col 56}{space 4}-.0022256{col 69}{space 3} .0019148
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}-4.399262{col 28}{space 2} 6.429271{col 39}{space 1}   -0.68{col 48}{space 3}0.497{col 56}{space 4}-17.34071{col 69}{space 3} 8.542188
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 14}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}  Absorbed FE{col 15}{c |} Categories{col 28} - Redundant{col 40}  = Num. Coefs{col 55}{c |}
{res}{col 1}{text}{hline 14}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text} state#c.year{col 15}{c |}{space 1}       47{col 28}{space 1}        0{col 40}{result}{space 1}       47{col 54}{text} {col 55}{c |}
{res}{col 1}{text}         year{col 15}{c |}{space 1}       19{col 28}{space 1}        0{col 40}{result}{space 1}       19{col 54}{text}?{col 55}{c |}
{res}{col 1}{text}{hline 14}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table_a5, tex append keep(divided_either ideociti urban income  lfullemp) label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X, Shares, X,  State-Specific Trends, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_a5.tex"'"':Table_a5.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_a5.txt", label"':seeout}

{com}. * table 2 column 2
. reghdfe civil_service_reform_ipe divided_governor divided_chamber sen_gov_share hs_gov_share dem_gov_share , a(state year )   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 5 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   5{txt},{res}     46{txt}){col 67}= {res}      2.42
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0496
{txt}{col 51}R-squared{col 67}= {res}    0.6342
{txt}{col 51}Adj R-squared{col 67}= {res}    0.6005
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0211
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.4274

{txt}{ralign 82:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}civil_service_~e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_governor {c |}{col 18}{res}{space 2} .2054005{col 30}{space 2}  .098754{col 41}{space 1}    2.08{col 50}{space 3}0.043{col 58}{space 4} .0066191{col 71}{space 3} .4041819
{txt}{space 1}divided_chamber {c |}{col 18}{res}{space 2}  .158467{col 30}{space 2} .0641517{col 41}{space 1}    2.47{col 50}{space 3}0.017{col 58}{space 4} .0293364{col 71}{space 3} .2875976
{txt}{space 3}sen_gov_share {c |}{col 18}{res}{space 2} .0043002{col 30}{space 2} .0037629{col 41}{space 1}    1.14{col 50}{space 3}0.259{col 58}{space 4}-.0032741{col 71}{space 3} .0118745
{txt}{space 4}hs_gov_share {c |}{col 18}{res}{space 2}-.0018915{col 30}{space 2} .0034828{col 41}{space 1}   -0.54{col 50}{space 3}0.590{col 58}{space 4} -.008902{col 71}{space 3} .0051191
{txt}{space 3}dem_gov_share {c |}{col 18}{res}{space 2}-.0005301{col 30}{space 2}  .001334{col 41}{space 1}   -0.40{col 50}{space 3}0.693{col 58}{space 4}-.0032152{col 71}{space 3} .0021551
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.127164{col 30}{space 2} .1494293{col 41}{space 1}    7.54{col 50}{space 3}0.000{col 58}{space 4} .8263784{col 71}{space 3}  1.42795
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}       state{col 14}{c |}{space 1}       47{col 27}{space 1}       47{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}        year{col 14}{c |}{space 1}       19{col 27}{space 1}        0{col 39}{result}{space 1}       19{col 53}{text} {col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table_a5, tex append keep(divided_governor divided_chamber)  label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X, Shares, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_a5.tex"'"':Table_a5.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_a5.txt", label"':seeout}

{com}. * table 2 column 4
. reghdfe civil_service_reform_ipe divided_governor divided_chamber ideociti urban income  lfullemp sen_gov_share hs_gov_share dem_gov_share , a(state##c.year year )   cl(state ) 
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 6 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}       830
{txt}Absorbing 2 HDFE groups{col 51}F({res}   9{txt},{res}     46{txt}){col 67}= {res}      1.68
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.1212
{txt}{col 51}R-squared{col 67}= {res}    0.8385
{txt}{col 51}Adj R-squared{col 67}= {res}    0.8109
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0251
{txt}{col 1}Number of clusters ({res}state{txt}) {col 30}= {res}        47{txt}{col 51}Root MSE{col 67}= {res}    0.2940

{txt}{ralign 82:(Std. Err. adjusted for {res:47} clusters in state)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}civil_service_~e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
divided_governor {c |}{col 18}{res}{space 2} .0660608{col 30}{space 2} .0789638{col 41}{space 1}    0.84{col 50}{space 3}0.407{col 58}{space 4}-.0928851{col 71}{space 3} .2250068
{txt}{space 1}divided_chamber {c |}{col 18}{res}{space 2} .0817127{col 30}{space 2} .0472017{col 41}{space 1}    1.73{col 50}{space 3}0.090{col 58}{space 4}-.0132993{col 71}{space 3} .1767247
{txt}{space 8}ideociti {c |}{col 18}{res}{space 2} .6163946{col 30}{space 2} .2480697{col 41}{space 1}    2.48{col 50}{space 3}0.017{col 58}{space 4} .1170563{col 71}{space 3} 1.115733
{txt}{space 11}urban {c |}{col 18}{res}{space 2} 3.696481{col 30}{space 2} 7.713077{col 41}{space 1}    0.48{col 50}{space 3}0.634{col 58}{space 4}-11.82914{col 71}{space 3}  19.2221
{txt}{space 10}income {c |}{col 18}{res}{space 2}  .044014{col 30}{space 2} .0840898{col 41}{space 1}    0.52{col 50}{space 3}0.603{col 58}{space 4}  -.12525{col 71}{space 3}  .213278
{txt}{space 8}lfullemp {c |}{col 18}{res}{space 2}  .237851{col 30}{space 2} .3781767{col 41}{space 1}    0.63{col 50}{space 3}0.532{col 58}{space 4}-.5233793{col 71}{space 3} .9990812
{txt}{space 3}sen_gov_share {c |}{col 18}{res}{space 2} .0008639{col 30}{space 2} .0029105{col 41}{space 1}    0.30{col 50}{space 3}0.768{col 58}{space 4}-.0049947{col 71}{space 3} .0067225
{txt}{space 4}hs_gov_share {c |}{col 18}{res}{space 2}-.0002772{col 30}{space 2}  .003079{col 41}{space 1}   -0.09{col 50}{space 3}0.929{col 58}{space 4}-.0064749{col 71}{space 3} .0059206
{txt}{space 3}dem_gov_share {c |}{col 18}{res}{space 2}-.0001528{col 30}{space 2}  .001029{col 41}{space 1}   -0.15{col 50}{space 3}0.883{col 58}{space 4}-.0022242{col 71}{space 3} .0019185
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-4.370231{col 30}{space 2} 6.464967{col 41}{space 1}   -0.68{col 50}{space 3}0.502{col 58}{space 4}-17.38354{col 71}{space 3} 8.643072
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 14}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text}  Absorbed FE{col 15}{c |} Categories{col 28} - Redundant{col 40}  = Num. Coefs{col 55}{c |}
{res}{col 1}{text}{hline 14}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}        state{col 15}{c |}{space 1}       47{col 28}{space 1}       47{col 40}{result}{space 1}        0{col 54}{text}*{col 55}{c |}
{res}{col 1}{text} state#c.year{col 15}{c |}{space 1}       47{col 28}{space 1}        0{col 40}{result}{space 1}       47{col 54}{text} {col 55}{c |}
{res}{col 1}{text}         year{col 15}{c |}{space 1}       19{col 28}{space 1}        0{col 40}{result}{space 1}       19{col 54}{text}?{col 55}{c |}
{res}{col 1}{text}{hline 14}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}{txt}
{com}. outreg2 using Table_a5, tex append keep(divided_governor divided_chamber ideociti urban income  lfullemp ) label   ctitle(Merit IPE)    addtext(State FE, X, Time FE, X, Shares, X,  State-Specific Trends, X) alpha(0.01, 0.05, 0.1) symbol(**, *, +)  nonotes addnote(SE clustered by `e(clustvar)', **p<.01; *p<.05; +p<.1)
{res}warning: addnote ignored in appended columns
{txt}{stata `"shellout using `"Table_a5.tex"'"':Table_a5.tex}
{browse `"C:\Users\k1780867\OneDrive - King's College London\Documents\Conference and Publications\1-civil-service-divided-govt\Paper intro merit system-separate\PSRM\replication"' :dir}{com} : {txt}{stata `"seeout using "Table_a5.txt", label"':seeout}

{com}. 
. 
{txt}end of do-file

{com}. exit, clear
